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Version 5.0 November 2005

Synphot User's Guide

Space Telescope Science Institute 3700 San Martin Drive Baltimore, Maryland 21218 help@stsci.edu

Operated by the Association of Universities for Research in Astronomy, Inc., for the National Aeronautics and Space Administration


User Support
For prompt answers to any question, please contact the STScI Help Desk. · E-mail: help@stsci.edu · Phone: (410) 338-1082 (800) 544-8125 (U.S., toll free)

World Wide Web
Information and other resources are available on the STSDAS World Wide Web site: · URL: http://www.stsci.edu/resources/software_hardware/stsdas

Revision History
Version 5.0 4.0 3.0 2.0 1.0 Date November 2005 December 1998 March 1995 September 1993 November 1990 Editors Vicki Laidler Howard Bushouse and Bernie Simon Howard Bushouse Howard Bushouse David Bazell

Contributors
Synphot is a large, complex software project based on Keith Horne's XCAL program which has benefited from the contributions of many people over the years, including David Bazell, Howard Bushouse, Vicki Laidler, Bernie Simon, and Anand Sivaramakrishnan. Special thanks to Susan Rose who assisted with the production of this version of the manual.

Citation
In publications, refer to this document as: Laidler et al, 2005, "Synphot User's Guide", Version 5.0 (Baltimore: STScI).

Send comments or corrections to: Space Telescope Science Institute 3700 San Martin Drive Baltimore, Maryland 21218 E-mail:help@stsci.edu


Table of Contents
List of Figures List of Tables Preface
.................................................................. vii ...................................................................... ix

..................................................................................... xi ...................................... 1 2 3 4 5 6

Chapter 1: About Synphot

1.1 Background..................................................................... 1.2 How Synphot Works ..................................................... 1.3 The Synphot Data Base .............................................. 1.4 How Accurate are the Synthetic Photometry Results from Synphot? ................................................... 1.5 Can Synphot be Used for Other Telescopes? .......

Chapter 2: Synphot and PyRAF

........................ 7

2.1 What is PyRAF? ............................................................ 7 2.2 General PyRAF advantages: ..................................... 8 2.3 Synphot specific examples: ........................................ 9
2.3.1 Replacing the "@filename" syntax ............................. 9 2.3.2 Replacing the "vzero" syntax .................................... 10 2.3.3 Generating a custom wavelength table .................... 11

Chapter 3: Using Synphot
3.2.1 3.2.2 3.2.3 3.2.4

.................................... 13

3.1 Synphot Tasks ............................................................. 13 3.2 Command and Argument Syntax ............................ 15
Syntax Examples ...................................................... Observation Mode .................................................... Spectrum .................................................................. Form ......................................................................... 3.3 Wavelength Table ....................................................... 3.4 Variable Substitution (VZERO) ................................ 15 16 18 21 25 26
iii


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Table of Contents

3.5 3.6 3.7 3.8

Reference Data............................................................ Table formats ............................................................... Using EPAR to edit task parameters ...................... About the Examples in This Manual .......................

27 28 28 28

Chapter 4: Cookbook

................................................ 31

4.1 Bandpasses .................................................................. 31 4.2 Spectra .......................................................................... 34 4.3 Photometry ................................................................... 37

Chapter 5: Task Descriptions

............................ 41 44 44 46 46 48 50 52 54 57 59 62 63 66 68 70 72 72 73 73 74 74 75 75

5.1 Bandpar ......................................................................... 42
5.1.1 Examples .................................................................. 5.2 Calcband ....................................................................... 5.2.1 Examples .................................................................. 5.3 Calcphot ........................................................................ 5.3.1 Examples .................................................................. 5.4 Calcspec ........................................................................ 5.4.1 Examples .................................................................. 5.5 Countrate ...................................................................... 5.5.1 Examples .................................................................. 5.6 Fitband ........................................................................... 5.6.1 Example .................................................................... 5.7 Fitspec ........................................................................... 5.7.1 Example .................................................................... 5.8 Fitgrid ............................................................................. 5.8.1 Examples .................................................................. 5.9 Genwave ....................................................................... 5.9.1 Examples .................................................................. 5.10 Grafcheck ................................................................... 5.10.1 Example .................................................................. 5.11 Graflist ......................................................................... 5.11.1 Examples ................................................................ 5.12 Grafpath ...................................................................... 5.12.1 Examples: ...............................................................


Table of Contents

v

5.13 Imspec ......................................................................... 76
If the input file is an image: ..................................... 76 If the input file is a table: ......................................... 77 Other parameters:................................................... 77 Examples ................................................................ 78 5.14 Mkthru .......................................................................... 78 5.14.1 Examples ................................................................ 80 5.15 Modeinfo ..................................................................... 80 5.15.1 EXAMPLES ............................................................ 81 5.16 Obsmode .................................................................... 81 5.16.1 Examples ................................................................ 82 5.17 Plband.......................................................................... 82 5.17.1 Examples ................................................................ 84 5.18 Plspec .......................................................................... 85 5.18.1 Examples ................................................................ 89 5.19 Plratio ........................................................................... 94 5.19.1 Examples ................................................................ 97 5.20 Pltrans.......................................................................... 98 5.20.1 Examples .............................................................. 100 5.21 Refdata ...................................................................... 101 5.22 Showfiles ................................................................... 102 5.22.1 Example ................................................................ 103 5.23 Thermback................................................................ 103 5.23.1 EXAMPLES .......................................................... 105 5.13.1 5.13.2 5.13.3 5.13.4

Chapter 6: Inner Workings

................................. 107

6.1 Syncalc ........................................................................ 107 6.2 Graph and Component Tables .............................. 109

Chapter 7: Calibration Using Synthetic Photometry .......................................

115

7.1 Principles of calibration ............................................ 115 7.2 Accuracy and errors in synthetic photometry ..... 118
7.2.1 Groundbased photometric systems ........................ 119 7.2.2 Vegamags............................................................... 119 7.2.3 HST bandpasses .................................................... 120


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Appendix A: On-Line Catalogs and Spectral Atlases ...............................................
A.1 HST Calibration Spectra .......................................... A.2 Kurucz 1993 Atlas of Model Atmospheres .......... A.3 THE HST/CDBS VERSION OF THE 1993 KURUCZ ATLAS ............................................... A.4 USE OF KURUCZ ATLAS WITH SYNPHOT ...... A.5 Bruzual Spectrum Synthesis Atlas ........................ A.6 Gunn-Stryker Spectrophotometry Atlas................ A.7 Bruzual-Persson-Gunn-Stryker Spectrophotometry Atlas ............................................ A.8 Jacoby-Hunter-Christian Spectophotometry Atlas ................................................................................ A.9 Bruzual-Charlot Atlas ................................................ A.10 Kinney-Calzetti Atlas............................................... A.11 Buser-Kurucz Atlas of Model Atmospheres ...... A.12 AGN Atlas .................................................................. A.13 Galactic Atlas ............................................................

121 122 125 126 129 131 132 132 135 138 139 139 142 142

Appendix B: Bibliography Index

.................................. 143

...................................................................................... 147


List of Figures
Figure 3.1: Standard photometric systems illustrated. ................. 24 Figure 4.1: Plband Plot of Johnson V and WFPC2 Bandpasses ............................................................................. 32 Figure 4.2: List of NICMOS Filters in File "nic_filters.lis" ............... 33 Figure 4.3: Bandpar Results for a List of NICMOS Filters ............. 34 Figure 4.4: Plotting Spectra with plspec ........................................ 35 Figure 4.5: countrate Parameters for STIS CCD Observation ...... 36 Figure 4.6: Predicted STIS CCD Spectrum Produced by countrate ............................................................................. 37 Figure 4.7: Calcphot Results for a WFPC2 F439W Observation .............................................................................. 38 Figure 4.8: Calcphot Results for a NICMOS F160W Observation .............................................................................. 39 Figure 4.9: Commands for Plotting Redshifted Spectra and UB Bands .......................................................................... 39 Figure 4.10: Plots of Redshifted Spectra and UB Bandpasses ..... 40 Figure 4.11: Using calcphot to Compute U-B Colors of Redshifted Spectra .............................................................. 40 Figure 5.1: Bandpar Parameters ................................................... 43 Figure 5.2: Calcband Parameters ................................................. 44 Figure 5.3: Calcphot Parameters .................................................. 46 Figure 5.4: Sample Calcphot Run ................................................. 49 Figure 5.5: Second Sample Calcphot Run .................................... 49 Figure 5.6: Calcspec Parameters .................................................. 51 Figure 5.7: FOS Count Rate Spectrum of G191-B2B ................... 53 Figure 5.8: WFPC2 Blackbody Spectra ......................................... 54 Figure 5.9: Countrate Task Parameters ........................................ 55 Figure 5.10: Example Countrate Parameter Settings .................... 57

vii


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List of Figures

Figure 5.11: Plot of Countrate Example Spectrum ........................ 58 Figure 5.12: Second Countrate Example Parameter Settings ...... 59 Figure 5.13: Fitband Parameters ................................................... 60 Figure 5.14: Results from Example Fitband Run .......................... 63 Figure 5.15: Fitspec Parameters ................................................... 64 Figure 5.16: Example Fitspec Parameter Settings ........................ 67 Figure 5.17: Results from Fitspec.................................................. 68 Figure 5.18: Fitgrid Parameters ..................................................... 69 Figure 5.19: Fitgrid Results ........................................................... 71 Figure 5.20: Genwave Parameters ............................................... 72 Figure 5.21: Imspec Parameters ................................................... 76 Figure 5.22: Mkthru Parameters .................................................... 79 Figure 5.23: Plband Parameters ................................................... 83 Figure 5.24: Results of First Sample Plband Run ......................... 84 Figure 5.25: Results of Second Sample Plband Run .................... 85 Figure 5.26: Plspec Parameters .................................................... 86 Figure 5.27: Plspec Results .......................................................... 90 Figure 5.28: Results from Second Sample Plspec Run ................ 91 Figure 5.29: Plspec Comparison of STIS Sensitivities .................. 92 Figure 5.30: Plotting Calcphot Results .......................................... 93 Figure 5.31: Distribution of Detected Counts ................................ 94 Figure 5.32: Plratio Parameters .................................................... 95 Figure 5.33: Sample Plratio Output ............................................... 97 Figure 5.34: Pltrans Parameters ................................................... 98 Figure 5.35: Results from Sample Pltrans Run ........................... 100 Figure 6.1: Structure of Instrument Graph Table ......................... 111 Figure 6.2: Structure of Component Lookup Table ..................... 112


List of Tables
Table 3.1: Primary Passband and Spectral Computation and Plotting Tasks.................................................................... 14 Table 3.2: Passband and Spectral Fitting Tasks ........................... 14 Table 3.3: Utility Tasks .................................................................. 14 Table 3.4: Passband Functions ..................................................... 18 Table 3.5: Spectrum Functions ..................................................... 20 Table 3.6: Reddening Laws Used by ebmvx ................................. 21 Table 3.7: Forms ........................................................................... 22 Table 3.8: Wavelength Units ......................................................... 25 Table 3.9: vzero Examples ............................................................ 27 Table 3.10: Parameters in refdata Pset ......................................... 27 Table 5.1: Bandpar Photometric Parameters ................................ 42 Table 5.2: Calcband Output Keywords .......................................... 45 Table 5.3: Functions Supported by Calcphot ................................ 47 Table 5.4: Calcphot Output Table Columns .................................. 48 Table 5.5: Error Type Codes for Plspec ........................................ 88 Table 6.1: Syncalc Functions ...................................................... 109 Table 6.2: Thermal Emissivity Table. ......................................... 113 Table 6.3: The emissivity table also contains some crucial information in header keywords: ................................. 114 Table A.1: CDBS Flux Standards with Columns in Order of Preference.......................................................................... 124 Table A.2: HST Calibration Spectra ............................................ 125 Table A.3: Grid of temperatures for the models .......................... 126 Table A.4: Wavelength coverage for the models ........................ 126 Table A.5: Sample FITS Header from Kurucz 93 Model ............ 128 Table A.6: Suggested models for specific stellar types ............... 130

ix


x

List of Tables

Table A.7: Bruzual Synthetic Spectral Atlas ................................ 131 Table A.8: Bruzual-Persson-Gunn-Stryker Spectral Atlas ........... 133 Table A.9: Jacoby-Hunter-Christian Spectral Atlas ..................... 136 Table A.10: Kurucz K1200 Library .............................................. 140 Table A.11: BK Atlas ................................................................... 141


Preface
This Guide describes the Space Telescope Science Data Analysis System (STSDAS) synthetic photometry (synphot) software package. STSDAS is developed and maintained by the STSDAS group at STScI and is an external package layered on the Image Reduction and Analysis Facility (IRAF), which is developed and maintained by NOAO. synphot is therefore portable to any host architecture supported by IRAF. synphot, like all other IRAF tasks, also runs under PyRAF, the new Python-based command language for IRAF. In order to run synphot, you will need to have IRAF, STSDAS, TABLES (another IRAF package maintained by the STSDAS group at STScI), and the data files associated with synphot installed on your machine. You may also wish to have PyRAF installed. You can obtain these packages from:
Package IRAF Download from http://iraf.noao.edu/iraf-homepage.html or call (520)318-8160 STSDAS TABLES PyRAF synphot data http://www.stsci.edu/resources/software_hardware/stsdas http://www.stsci.edu/resources/software_hardware/tables http://www.stsci.edu/resources/software_hardware/pyraf http://www.stsci.edu/resources/software_hardware/stsdas/synphot

A variety of additional documentation is available for synphot, IRAF, and PyRAF. For more information, please consult the following documents:

xi


xii

Preface

For help with
IRAF cl or STSDAS PyRAF Installing synphot data files HST keywords for synphot synphot problems

Consult
The STSDAS User's Guide PyRAF tutorial, programmer's guide, and FAQ Data installation guide Synphot Data User's Guide synphot FAQ

Available from:
www.stsci.edu/resources/software_hardware/stsdas

stsdas.stsci.edu/pyraf/doc/index.html

ftp.stsci.edu/pub/software/stsdas/refdata/synphot /stdata_install.ps www.stsci.edu/resources/software_hardware/stsdas/ synphot/SynphotDataGuide.html http://www.stsci.edu/resources/software_hardware/ stsdas/synphot/FAQ

If you have questions or problems using IRAF, PyRAF, STSDAS, or synphot, you may also contact the STScI Help Desk by sending E-mail to help@stsci.edu.


CHAPTER 1:

About Synphot
In this chapter. . .
1.1 Background 1.2 How Synphot Works 1.3 The Synphot Data Base 1.4 How Accurate are the Synthetic Photometry Results from Synphot? 1.5 Can Synphot be Used for Other Telescopes? / / / / / 2 3 4 5 6

The Space Telescope Science Data Analysis System (STSDAS) synphot package simulates photometric data and spectra as they are observed with the Hubble Space Telescope (HST). Synphot tasks will: · Plot HST sensitivity curves and calibration target spectra. · Predict count rates for observations in any available HST instrument mode. · Compute the photometric calibration for any HST instrument mode. · Examine photometric transformation relationships among the various HST observing modes as well as conventional photometric systems, such as Johnson UBV. Synphot can help HST General Observers (GOs) prepare Phase I and Phase II observing proposals. Synphot's cross-instrument simulation ability is useful for planning and optimizing HST observing programs. Synphot provides an easy way to examine the transmission curve of the HST Optical Telescope Assembly (OTA), sensitivity curves for all modes of observing with the science instruments, and flux distributions of HST calibration targets.

1


2

Chapter 1: About Synphot

Passbands for standard photometric systems are available, and users can incorporate their own filters, spectra, and data. A powerful spectrum calculator can create complicated composite spectra from various parameterized spectrum models, grids of model atmosphere spectra, and atlases of stellar spectrophotometry. The rest of this chapter contains introductory information regarding the synphot package, and Chapter 2 provides a synphot user's introduction to PyRAF, the new Python-based command language for IRAF. Chapter 3 discusses the basic features that are common to most synphot tasks, and Chapter 4 demonstrates some simple examples of how they are used by the tasks. Detailed explanations of each task and examples of their use are given in Chapter 5. Chapter 6 contains a more in-depth look at internal operations, and Chapter 7 provides a mathematical description of some basic synthetic photometry concepts and its role in calibrating the HST instruments. Many of the examples contained in Chapter 4 and Chapter 5 make use of spectral data from the on-line catalogs of spectral atlases maintained at STScI. These atlases are also available to off-site synphot users. Appendix A:On-Line Catalogs and Spectral Atlases contains detailed information on the origin and contents of these atlases, as well as installation information for off-site users.

1.1

Background
The synphot package is modeled on Keith Horne's XCAL software--a suite of Fortran subroutines designed to be used as a dynamic throughput generator using files stored in the HST Calibration Data Base System (CDBS). Because the HST has a vast number of interrelated observing modes, it is impractical and inefficient to derive and maintain an independent calibration for every possible instrument configuration. Rather than restrict calibrations to a smaller number of core modes, the alternative is to provide a software tool that can generate the throughput function for any HST observing mode; this is how XCAL and synphot are implemented. Throughput functions and calibration data files for specific observing modes are dynamically generated as needed. This approach reduces the number of calibration data files that must be created and maintained to a manageable level, and ultimately saves considerable observing time since information from calibration observations in one mode can be easily transferred to other closely related modes. Additional information and discussion of the synthetic photometry approach to HST calibration can be found in Koornneef et al. (1986) and Horne (1988).


How Synphot Works

3

1.2

How Synphot Works
The basic concepts, data structures, and software needed for dynamic throughput generation are discussed in detail by Horne, Burrows, and Koornneef (1986). Briefly, the throughput calibration of the HST observatory is represented in a framework consisting of: · Component throughput functions for every optical component (e.g., mirror, filter, polarizer, disperser, and detector). · A configuration graph describing the allowed combinations of the components. A particular observing mode is specified by a list of keywords, which might be familiar names of filters, detectors, and gratings. The keywords are used to trace a path through the observatory configuration graph, thereby translating the keyword list into a list of pointers to data files that contain the individual component throughput functions. The grand throughput function of the requested observing mode is formed by multiplying together the individual component throughputs at each wavelength. (See Chapter 6 for more details on the functioning of the observing mode expression evaluator and the internal structure and functioning of the configuration graph and component throughput tables.) To retrieve a particular HST passband, you furnish the passband generator with a couple of keywords, for example "WFPC2,4,F336W". The passband generator uses the keywords to trace a path through the graph, multiplies together the component passbands it encounters along the way, and returns the passband evaluated on a particular wavelength grid. Passbands can then be convolved with spectral data to simulate HST observations of particular targets. Spectra may come from existing files containing lists of fluxes as a function of wavelength, or may be dynamically generated (individually or in combination) as simple blackbody, power-law, or Hydrogen continuum emission spectra of chosen temperatures and slopes. Most synphot task data I/O is done via FITS files with binary table extensions. The HST instrument graph, component lookup, and component throughput tables are all in this format. All output files created by the synphot tasks are either in FITS format or STSDAS table format, depending on the extension specified for the output filename. Input data files, such as passband throughput and spectral data files, may be in either FITS files, STSDAS table format, or plain ASCII text tables.


4

Chapter 1: About Synphot

Warning: STSDAS table format is a binary file format, and so care must be taken when working on multiple platforms with different endian architectures for floating point representation -- for example, Solaris and Linux. For this reason, we recommend that the use of STSDAS tables be deprecated, and that FITS binary tables be used instead. Existing STSDAS tables can easily be converted to FITS using the TABLES command tcopy mytable.tab mytable.fits

1.3

The Synphot Data Base
As you may have already realized from the preceding discussion, the synphot package is entirely data driven. That is, no information pertaining to the physical description of instruments or their throughput characteristics is contained within the software, but is instead contained within an external "database." These data must be available in order to run any synphot tasks. The data set contains the HST instrument graph, component lookup, and component throughput tables, which are maintained and stored within the HST Calibration Data Base System (CDBS) at STScI. New versions of these tables are created whenever new or updated calibration information becomes available for the HST instruments. Users at STScI have automatic access to the synphot data set on all science computing clusters. New versions of any of the tables become available within about 24 hours after they are installed in the CDBS. Because the data set is not currently distributed along with the STSDAS software, off-site users must retrieve and install it separately before they will be able to use synphot. This can be done in one of two ways: · Tar Files: Every time a new version of the STSDAS software is released, a "snapshot" of the current synphot data set is copied into a few tar files, which can then be retrieved, unpacked, and installed on your system. The STSDAS Site Manager's Installation Guide contains instructions for doing this. This method offers the convenience of having to transfer only a few files and automatically creates the necessary directory tree for the data. On the other hand, this "snapshot" is made only once or twice a year and therefore may not contain the latest data for the HST instruments. · Individual CDBS Files: An alternative method is to transfer the individual tables from the /data/cdbs1/ directory at ftp.stsci.edu (see below), which is updated on a daily basis.


How Accurate are the Synthetic Photometry Results from Synphot?

5

The best method is perhaps a combination of the two: first-time installers may wish to use the "snapshot" tar files to initially create and populate the directory structure, and then periodically check the CDBS area at STScI for updates to individual tables. The latest versions of individual tables can be obtained via anonymous ftp in the /data/cdbs2/ directory and its associated subdirectories on node ftp.stsci.edu, or through the web site
http://www.stsci.edu/hst/observatory/cdbs/cdbs_throughput.html.

The instrument graph and component lookup tables are contained in the mtab subdirectory and are named *_tmg.fits and *_tmc.fits. The component throughput tables are logically grouped into subdirectories of /data/cdbs2/comp/ corresponding to each of the HST instruments (acs,fgs, foc, fos, hrs, hsp, nicmos, nonhst, ota, stis, wfpc, and wfpc2). Component throughput table names contain a three digit suffix indicating their version number. You can determine which tables are new by comparing either their names or creation dates with the corresponding set of tables installed at your site.

1.4

How Accurate are the Synthetic Photometry Results from Synphot?
Because the synphot package is entirely data driven, the accuracy of its results depends entirely on the accuracy of the bandpass sensitivity curves and zero points in the synphot database. The accuracy of these values is dependent on the instrument and photometric system under consideration. As a general rule of thumb, synthetic photometry involving photometric systems that have been defined from the ground, or photometry that is given in vegamags, should only be considered accurate to about 5 percent. To achieve better accuracy, you should perform your own calibrations using known standard stars. (For a discussion of vegamags and other magnitude units, see section 3.2.4.) Synthetic photometry with the stable HST instrumentation, flying above the atmosphere, when used in HST instrument natural systems, without reference to vegamags, can achieve accuracy much better than 5%; for example ACS broad band filters <=1% (De Marchi et al 2004). For more detail, see Chapter 7:Calibration Using Synthetic Photometry, and the HST Data Handbook.


6

Chapter 1: About Synphot

1.5

Can Synphot be Used for Other Telescopes?
Because the tasks in the synphot package are data driven, instrument observing modes can be changed and new instruments added without changing the software. To use synphot with non-HST instruments or components you would need to modify (or rebuild) only the instrument graph and component lookup tables. Synphot requires: · One instrument graph table. · One component lookup table. · One thermal component lookup table (only needed for thermal background calculations) · One throughput table for each telescope and instrument component that appears in the graph and component lookup tables. The names of the instrument graph and component lookup tables to be used by the synphot tasks are set by the parameters grtbl and cmptbl, in the refdata parameter set. The names of the individual component throughput tables are contained in the component lookup table and are located automatically when you run a task. See Chapter 6 for details on the structure of these tables. To build your own instrument graph and component lookup tables it is perhaps easiest to either start with a copy of the existing HST tables and modify or add to them, or at least use the HST tables as a model for your own tables. To make use of your own custom graph and component lookup tables in synphot, just change the values of the grtbl and cmptbl parameters (and the telescope area parameter, if appropriate) in the refdata parameter set.


CHAPTER 2:

Synphot and PyRAF
In this chapter. . .
2.1 What is PyRAF? / 7 2.2 General PyRAF advantages: / 8 2.3 Synphot specific examples: / 9

In this chapter we will illustrate some uses of synphot in the PyRAF environment, and demonstrate some techniques that can make scripting and data processing more efficient.

2.1

What is PyRAF?
PyRAF (Greenfield & White, 2000) is a new command language for IRAF that is based on Python. It has a number of advantages over the IRAF CL. Most importantly, with few exceptions, it allows use of exactly the same syntax that the IRAF CL accepts; but it is a Python module, so all python capabilities are available on the command line. Some of the advantages that it provides are: · true command line recall (with arrow key editing) · command and filename completion · GUI-based graphics windows, previous plot recall, multiple graphics windows · GUI epar editor with display of help in separate window

7


8

Chapter 2: Synphot and PyRAF

· IDL-like capabilities, when used together with numarray and PyFITS modules · true error handling for scripts (shows which line the script fails at when errors occur) · can script IRAF tasks in Python language · exception handling capability Since PyRAF is so highly compatible with the examples shown in this handbook will Minor differences include the user prompt appearance. More information on PyRAF can be found the IRAF CL, virtually all of work the same for PyRAF. and the graphics windows at:

http://www.stsci.edu/resources/software_hardware/pyraf

For an introduction to PyRAF for IRAF users, and a general comparison of similarities and differences, see the Pyraf Tutorial and PyRAF FAQ available on the documentation pages from the above URL.

2.2

General PyRAF advantages:
· Simpler epar interface for XWINDOWS Under PyRAF, epar pops up a GUI window for editing task parameters. This can be particularly useful for synphot tasks that have many task parameters. · true command line recall (with arrow key editing) Command line recall and editing are particularly useful when working with synphot interactively and experimenting with a variety of task parameters. · Tab filename completion PyRAF provides tab filename completion. This can be particularly useful for selecting a reference spectrum from the crcalspec$ directory that contains dozens of available calibration spectra. · Simpler specification of parameterized keywords and psets In the CL, observation modes containing a parameterized keyword (such as cont# for WFPC2) can be entered directly in epar, but must be enclosed in quotes if they are entered on the command line. PyRAF will accept parameterized keywords without surrounding them in quotes. Editing psets (parameter sets) is easy in PyRAF:


Synphot specific examples:

9

psets are presented as buttons in the epar widget. Selecting the button pops up a new epar window. In the cl, special key combinations must be used to begin and end the editing of psets.

2.3

Synphot specific examples:
These examples use Python syntax. In Python, indentation matters: instead of begin and end constructs, Python uses indentation to manage loops. A loop begins with a for statement ending in a colon: for item in mylist: or for i in range(20): In an interactive PyRAF session, the Python interpreter will respond to these lines by changing the prompt to three dots ( ... ) indicating that it is waiting for indented lines to be executed inside the loop. To complete the loop, simply type a carriage return to produce a blank line. The Python line continuation character is a backslash ("\"). We've used it in these examples for typesetting reasons, but you generally should not need to use it in interactive sessions.

2.3.1 Replacing the "@filename" syntax
Many synphot tasks will accept a file containing a list of filenames, one per line, to be processed. Using the scripting capabilities of Python, PyRAF can essentially duplicate this functionality without the need to generate an intermediate file. Example: Suppose you want to run calcspec to predict the observed spectrum for a variety of potential target spectra (which you have collected in the form of FITS files in the directory /data/planning/targets) as observed through the ACS wide field camera with the f606w filter. After entering PyRAF, you need to import the synphot package in order to use the Python scripting capabilities --> from pyraf.iraf import stsdas,hst_calib,synphot To generate a list of the target filenames, you'll need the python package glob. --> import glob --> mytargets=glob.glob('/data/planning/targets/*.fits')


10

Chapter 2: Synphot and PyRAF

The variable mytargets is now a list of filenames, which you can look at in a print statement, use in a for loop, and operate on to produce the desired task parameters. --> for targ in mytargets: ... iraf.calcspec(spectrum='band(acs,wfc1,f606w)*'+targ,\ output='output_'+targ,form='flam') One significant difference between using this syntax, and the synphot @filename syntax, is the handling of the wavelength table on which the calculations are performed. (See Section 3.3, "Wavelength Table," on page 25 for a more detailed discussion of the wavelength table.) In a python loop, calcspec will be invoked separately for each input spectrum, and will therefore determine the optimal wavelength table to be used independently for each input spectrum. Using the @filename syntax invokes calcspec only once, and calcspec determines the optimal wavelength table based on the first input spectrum only, and uses it for all spectra in the list. This default behavior is desirable in some cases and undesirable in others. If you want to ensure that all objects are run with the same wavelength table, you can generate it ahead of time and use it as another parameter in the call. --> genwave mywavecat.fits 2000 10000 1.5 A/pixel = 1.5 Mean km/s/pixel = 90.5 Range = 2000. to 10000. Number of Pixels = 5334 --> for targ in mytargets: ... iraf.calcspec(spectrum='band(acs,wfc1,f658n)*'+targ,\ output='output_'+targ,form='flam',wavetab='mywavecat.fits') Note that, when running PyRAF interactively, it's perfectly possible to mix the use of ordinary IRAF style calls with the use of Python-scripted style calls. This allows you to use the terse interactive syntax most of the time, and use the more verbose scripted style only when necessary. (In a Python script, you cannot mix the styles and must use the Python style throughout.)

2.3.2 Replacing the "vzero" syntax
Some synphot tasks allow you to run in a loop using the vzero variable to specify values to substitute for $0 in another input parameter. If you use this ability infrequently enough that you find its syntax hard to remember, you might prefer to build a loop in python instead.


Synphot specific examples:

11

Example: Let's look at the last example for calcspec, which illustrates the use of vzero, and use a python command instead. The goal is to generate a series of blackbody functions, covering the range of temperatures from 5000 to 20000 in steps of 1000K, as observed through the WFPC2 F439w filter with a flux of 1200 counts. Here's the pure-synphot command: sy> calcpsec "rn(bb($0),band(wfpc2,f439w,a2d7),1200,counts) \ bbody.fits form=flam vzero="5e3-20e3x1e3" Here's the python looping command: --> for t in range(5000,21000,1000): rncmd="rn(bb(%d),band(wfpc2,f439w,a2d7),1200,counts)"%t iraf.calcspec(spectrum=rncmd,out='bbody.fits',form='flam') Note that the range runs from 5000 to 21000: this is because python ranges are defined including the low end but excluding the high end. Because this invokes calcspec separately for each case, using the python loop produces a single FITS file with 16 extensions, each containing a table with columns for wavelength and flux. The vzero method produces a FITS file with a single table, with one column for wavelength and 16 columns for flux.

2.3.3 Generating a custom wavelength table
The synphot task genwave can be used to generate wavelength tables with uniform spacing; but what if non-uniform spacing is desired? In this case, we can use PyFITS to create a new table for use with synphot. Suppose we want a wavelength set that ranges from 2000 to 8000, with single Angstrom spacing over most of the range, but 0.1 Angstrom spacing around the OIII forbidden lines at 4959 and 5007. First, we import numarray and create the three pieces separately:
--> import numarray --> lowwave=numarray.arange(2000.,4950.) --> hiwave=numarray.arange(5010.,8000.) --> midrange=numarray.arange(4950.,5010.,0.1)

then concatenate them
--> wave=numarray.concatenate( (lowwave,midrange,hiwave) )

Now we need to create a FITS file from this array. First we import PyFITS and define a column:
--> import pyfits --> col1=pyfits.Column(name='wavelength',\ unit='angstroms',format='E',array=wave)


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Chapter 2: Synphot and PyRAF

Then construct a table from the column; a list of HDUs including the table, and write the new file out to disk.
--> tabhdu=pyfits.new_table([col1]) --> tabhdu.writeto('mywaveset.fits')

The FITS file mywaveset.fits can now be used as a wavelength table in a synphot task.


CHAPTER 3:

Using Synphot
In this chapter. . .
3.1 Synphot Tasks 3.2 Command and Argument Syntax 3.3 Wavelength Table 3.4 Variable Substitution (VZERO) 3.5 Reference Data 3.6 Table formats 3.7 Using EPAR to edit task parameters 3.8 About the Examples in This Manual / / / / / / / / 13 15 25 26 27 28 28 28

This chapter describes the basic structure of the synphot package, and how the tasks are used. Most of the chapter is devoted to a discussion of common parameters and command syntax. The use of each individual task is described in detail in Chapter 5.

3.1

Synphot Tasks
There are three categories of tasks in the synphot package. · Tasks that create, manipulate, and plot passbands and spectra (Table 3.1). This is the main group of tasks. · Tasks that fit model passbands and spectra to spectrophotometric and photometric data (Table 3.2). These tasks are intended to be used for passband reconstruction. · General utility tasks that convert data and check or maintain the instrument graph and component tables (Table 3.3).

13


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Chapter 3: Using Synphot Table 3.1: Primary Passband and Spectral Computation and Plotting Tasks.
Task calcband plband calcspec plspec countrate calcphot bandpar plratio pltrans thermback Function Calculate a model passband Plot passband data Calculate a model spectrum Plot spectral and photometric data Calculate the response of HST instruments to model spectra and passbands Calculate synthetic photometry for model spectra and passbands Calculate photometric parameters of a passband Plot the ratio of observed and synthetic spectral data Plot photometric transformation (color-color, color-mag) diagrams Calculate a model thermal background

Table 3.2: Passband and Spectral Fitting Tasks
Task fitband fitspec fitgrid Function Fit a model passband to known throughput data Fit a model spectrum to known spectral data Fit a spectrum by interpolating within a grid of model or observed spectra, such as a spectral atlas

Table 3.3: Utility Tasks
Task imspec genwave grafcheck graflist grafpath mkthru modeinfo obsmode showfiles Function Convert IRAF/STSDAS images to and from STSDAS or FITS tables Generate a wavelength set Check an instrument graph table for bad rows List components downstream from a given component in an instrument graph table Print ordered list of throughput files used for a specified obsmode Converts an ASCII, FITS, or STSDAS table into a throughput table for installation into CDBS Lists available keywords for an instrument or filter system & explains their use List the valid observation mode keywords for an instrument Print filenames used in a synphot expression


Command and Argument Syntax

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3.2

Command and Argument Syntax
There are five parameters that are common to many of the primary synphot tasks: · Observation mode (obsmode) - Passband to be calculated (page 16). · Spectrum (spectrum) - Spectrum to be calculated (page 18). · Form (form) - Units of the output data; for example, counts or magnitudes (page 21). · Wavelength table (wavetab) - Wavelength grid on which passband and spectrum will be calculated (page 24). · Reference data parameters (refdata) - Pointer to reference data for instrument graph and component lookup tables (page 27). Each of these parameters is discussed in detail in the following sections, but before getting into details, the next section provides some examples of general command syntax to show how some of these parameters are typically used.

3.2.1 Syntax Examples
In the command:
sy> plband acs,hrc,f555w

the string "acs,hrc,f555w" is the observation mode, or obsmode, and specifies that a passband be calculated by taking the product of the individual throughputs of the Advanced Camera for Surveys (ACS) high resolution camera (hrc), the f555w filter, the detector sensitivity, and the HST Optical Telescope Assembly (OTA). The OTA throughput is included automatically whenever an HST instrument mode is specified. (Whenever an obsmode involving the Faint Object Camera (FOC), Faint Object Spectrograph (FOS), or High Resolution Spectrograph (HRS) is specified, the throughput for COSTAR, the Corrective Optics Space Telescope Axial Replacement, is also included automatically.) In this example, where the settings of the wavetab and refdata task parameters were not specified, the HST default values will be used. The command:
sy> calcband acs,hrc,f555w acs_f555w.fits

will calculate that same passband and write the resulting data to the table acs_f555w.fits, which will contain columns of wavelength and throughput values. The next example simply plots the spectrum of the star HZ 44:
sy> plspec "" crcalspec$hz44_stis_001.fits flam


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Chapter 3: Using Synphot

Here the obsmode is set to a null string ("") so that the spectrum is plotted without being multiplied by a passband. The spectral data for HZ 44 come from a library of HST calibration spectra in the directory referenced by the IRAF environment variable crcalspec$, so the spectrum parameter is simply the name (including the directory path) of the table. The form parameter is set to "flam", which specifies that the spectrum is to be plotted in units of f (ergs/s/cm2/å). The last example will calculate the expected countrate for observing the star HZ 44 using the Wide Field Planetary Camera 2 (WFPC2) CCD number 1 and F439W filter:
sy> calcphot wfpc2,1,f439w,a2d7 crcalspec$hz44_stis_001.fits counts

Here the obsmode is the WFPC2 chip 1 with the F439W filter and the A-to-D gain setting of 7. The form parameter is "counts". This will multiply the combined HST+WFPC2+F439W throughput with the spectrum of HZ 44 and compute the resulting count rate (6287 DNs per second!).

3.2.2 Observation Mode
The observation mode (obsmode) parameter defines the passband, i.e., the wavelength-dependent sensitivity curve of the photometer or spectrophotometer. The obsmode parameter can also be used to specify a color index, or a series of passbands or color indexes, as described further below. The obsmode is usually given as a string of keyword arguments to the band function, for example "band(wfpc2,4,f555w)". The list of keywords specifies a light path through the telescope and an instrument. The modeinfo task can be used to obtain a current list of all the valid keyword names for the HST instruments. The keywords may appear in any order and are not case sensitive. As a convenience to users, if the obsmode expression consists of a single call to the band function, only the arguments to the function need be given. For example, the obsmode "band(wfpc2,4,f555w)" can also be given as just "wfpc2,4,f555w". Passbands can also be read directly from files. Passband files may be in the form of either ASCII text, FITS binary tables, or STSDAS binary tables and must contain, at minimum, columns of wavelength and throughput values. The synphot expression calculator determines whether a file contains a passband or a spectrum by looking for the throughput column. If the file contains a throughput column it is read as a passband; if not, it is read as a spectrum. If the file is an STSDAS or FITS table, synphot will look for columns named "WAVELENGTH" and "THROUGHPUT". Since ASCII text files do not contain column names, synphot assumes that the wavelengths are in


Command and Argument Syntax

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the first column and you must supply the column number of the throughput data in brackets at the end of the file name. For example, if the throughput data are in column 2 of the text file my_filter.dat, then the obsmode is specified as "my_filter.dat[2]". See Chapter 6:Inner Workings for more details on the allowed formats of input tables and how the synphot expression evaluator handles them. A series of passbands may be processed in a single task execution by setting the obsmode parameter to "@filename", where filename is the name of an ASCII text file containing a list of desired passbands, one per line. The passbands designated on each line may be composed of either calls to the band function or specific file names containing throughput data. Color indices are defined by setting the obsmode parameter to MODE1­MODE2, where MODE1 and MODE2 are specifications for the two passbands. For example, "band(wfpc2,f439w)-band(wfpc2,f555w)" gives you the WFPC2 color index that approximates B-V. The observation mode can also be a part of a larger expression used to calculate either a passband or spectrum. The syntax of these larger expressions is explained below. The HST OTA transmissivity is included by default in the calculation of all HST-related observation modes. It can be included explicitly by adding the keyword ota or excluded by adding the keyword noota; for example "fos,blue,1.0,g130h,noota". All current HST instruments (except the FGS) have built-in corrective optics to compensate for the spherical aberration of the primary. For the first-generation instruments FOC, FOS, and GHRS, the HST instrument graph allows the inclusion of the effects of COSTAR on the wavelength-dependent sensitivity. This includes the product of the reflectivity curves for each pair of COSTAR mirrors for each of these instruments, as well as the effects on instrument throughput and sensitivity due to the improved point-spread function that is achieved with COSTAR. Like the OTA, the COSTAR effects on passbands and count rates are included by default for these instruments when using versions of the HST graph table dated 950224 (24 February 1995) and later. In earlier versions of the graph table, nocostar is the default. To explicitly include COSTAR, use the keyword costar anywhere within your obsmode string, e.g., "fos,red,4.3,g270h,costar". To exclude it, use the nocostar keyword. It is not necessary to explicitly exclude COSTAR for current generation instruments; it will be excluded by default. In addition to the HST instruments, filters, and gratings, the synphot graph table also contains entries for various standard passbands that are not specific to HST. The ANS (Astronomical Netherlands Satellite), WF/PC-1 Baum, Cousins RI, Johnson UBVRIJK, Landolt UBVRI, Stromgren uvby, Walraven VBLUW, Sloan Digital Sky Survey ugirz, and the Bessell, Kitt Peak, and Steward Observatory JHK bands are included. The modeinfo


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Chapter 3: Using Synphot

task will return a complete list of available non-HST passbands. Note that the Landolt (1983) UBVRI system is made up of the Johnson UBV and the Cousins RI passbands. Non-HST filters are specified using the name of the filter system, followed by the desired band name, e.g., "stromgren,u" or "cousins,i". If the name of the filter system is omitted for any of the common UBVRIJHK filters, the defaults are Johnson UBV, Cousins RI, and Bessell JHK. The synphot tasks will also accept function expressions in the obsmode parameter. The available passband function expressions are shown in Table 3.4.
Table 3.4: Passband Functions
OBSMODE filename @filename band(obsmode) thru(filename) box(mu,width) em(mu,fwhm,totflux,units) gauss(mu,fwhm) lgauss(mu,fwhm) poly(mu,fwhm,a1,a2,...) Passband Name of an ASCII text file or STSDAS table containing columns of wavelength and throughput values. Name of an ASCII text file containing one string of passband commands per line. Constructs a passband associated with the specified obsmode Used when the filename might be interpreted as a number or contain arithmetic operators or be interpreted as a spectrum. Otherwise just use the filename. Rectangular window centered on wavelength mu with width width; both arguments in Angstroms. Emission line centered on wavelength mu with a Gaussian profile, full width half maximum fwhm, and total flux totflux specified in units Gaussian with mean wavelength mu and full width half maximum fwhm; both arguments in Angstroms. Gaussian in log wavelength space. A passband that is a function of Legendre polynomials. The value of this function is (1+P) if P is positive and exp(P) if P is negative. P is the sum of up to ten Legendre polynomials with the specified coefficients. The independent variable in the polynomial is (wave - mu) / fwhm, where wave is the wavelength. The same as poly (above), but values of mu and fwhm are calculated from the passband band and the passband is implicitly multiplied by the tilt function.

tilt(band,a1,a2,...)

More than one function expression can be included in an obsmode. For example, the following command will calculate a Gaussian, multiply it by a third-order polynomial, and write the results to a table called out.fits.
sy> calcband "tilt(gauss(5000,1000),0,1,3)" out.fits

3.2.3 Spectrum
The spectrum parameter defines the spectrum to be created or operated upon for tasks such as calcphot, countrate, calcspec, plspec, and plratio. Spectra can be read in from disk files or calculated from analytic models. A powerful spectrum calculator allows you to construct


Command and Argument Syntax

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complicated composite spectra, apply or remove extinction, renormalize to a desired magnitude or flux, add and subtract spectra, and multiply spectra by passbands or constants. Filename specifications When reading a spectrum from a file, you have a choice of using ASCII text files, FITS tables, or STSDAS tables. When using FITS or STSDAS tables, synphot looks for the column names "WAVELENGTH" and "FLUX". If column units are not specified, units of Angstroms for wavelengths and units of "flam" (see "Form" on page 21) for fluxes are assumed. When using a text table, the wavelength and flux values must be in the first and second columns, respectively. Since text tables do not have column units definitions, wavelengths must be in units of Angstroms and fluxes in units of "flam". To process a series of spectra in sequence, set the spectrum parameter to "@filename", where filename is the name of an ASCII file containing the list of desired spectra, each one specified on a separate line of the file.

When using the @filename syntax, the task will generate the wavelength table to be used based on the first spectrum only, and will use this wavelength set for all calculations.

This will frequently provide different results than running the task for each spectrum in the sequence independently. If this is undesirable, one may either specify the wavelength table to be used for all calculations, or use the Python looping syntax (see"Replacing the "@filename" syntax" on page 9) to use the optimal set for each spectrum. Functional forms Table 3.5 lists the functional forms that can be used to generate synthetic spectra and to manipulate spectra read from a file. Blank spaces in a spectrum expression are not significant, except for the division operator, which must be surrounded by blanks so that it is not mistaken for part of a directory path name. Note that the pl function produces a power law spectrum in the units specified by the third argument. The exponent of the power law may change when converted to photlam space, which is the native form for all synphot calculations. The ebmv operator applies or removes extinction effects using the interstellar extinction curve from Seaton (1979), which is based on an adopted value of R = AV / E(B­V) = 3.20. For wavelengths between 1000 and 3704 å, the analytic fits given in Seaton's Table 2 are used to compute


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Chapter 3: Using Synphot Table 3.5: Spectrum Functions

SPECTRUM
filename

Function Name of an ASCII text file, FITS table, or STSDAS table containing columns of wavelength and flux values. Name of an ASCII file containing one string of spectrum commands per line. Used when the filename might be interpreted as a number. Creates a constant spectrum of value val in units of form (fnu, flam, counts, etc.) Blackbody spectrum with specified temperature, in Kelvin. The flux of the spectrum is normalized to a star of solar radius at a distance of 1 kpc. Power-law spectrum of the form f ( / refval ) , where refval is in Angstroms. The spectrum is normalized to a flux of 1 in form units at refval. Continuum emission spectrum of an LTE slab of hydrogen at temperature temp (Kelvin) and column density colden (baryons/cm-2). Values of colden less than 80 are assumed to be log10(colden). The spectrum is normalized the same as the blackbody. Read a spectrum selected from catalog, according to the search criteria key1, ..., keyn. Interpolate a spectrum from catalog, selected by the search criteria key1, ..., keyn. Interpolate between two spectra in a list of spectra. The list is named by filename and the interpolation position within the list is specified by seq. For example, "3.5" means interpolate midway between the third and fourth spectra. Renormalize the spectrum spec to value with units form over the obsmode passband. The evaluator computes the integral of the spectrum over the specified passband and rescales the spectrum by the appropriate factor, forcing this integral to have the requested renormalized value. Redshift a spectrum by the amount z. Applies an extinction of val E(B ­ V) to a spectrum using the galactic ISM reddening law of Seaton (1979). Applies an extinction to the spectrum using one of a number of available reddening laws. Add, subtract spectra with automatic unit conversion, if needed. Multiply, divide by a passband (obsmode), constant, or ebmv, ebmvx functions.
expon

@filename spec(filename) unit(val,form) bb(temperature)

pl(refval,expon,form)

hi(temp,colden)

cat(catalog,key1,...) icat(catalog,key1,...) grid(filename,seq)

rn(spec,obsmode,value,form)

z(spectrum,z) ebmv(val)

embvx(val,law)

+*/

the extinction, while for wavelengths between 3704 and 10000 å, the extinction is computed by linear interpolation (in 1/ vs. magnitudes) within the tabulated values given in Seaton's Table 3. For wavelengths greater than 10000 å, the extinction is computed via a linear extrapolation of the tabulated optical values. The extended reddening function, ebmvx, supports a number of different reddening laws. The second argument selects the type of reddening law used to compute the extinction. The task supports three galactic reddening laws (gal1 to gal3) and one law each for the Small Magellanic Cloud (smc), Large Magellanic Cloud (lmc), and


Command and Argument Syntax

21

extra-galactic objects (xgal). The reddening law used in the ebmv function is the same as gal1. The laws are derived from the papers cited in Table 3.6.
Table 3.6: Reddening Laws Used by ebmvx
Reddening Law gal1 gal2 gal3 smc lmc xgal Citation Seaton (1979) MNRAS, vol. 187, p. 75 Savage & Mathis (1979) ARA&A, vol. 17, pp. 73-111 Cardelli, Clayton & Mathis (1989) ApJ vol. 345, pp.245-256 Prevot, et al. (1984) A&A vol. 132, pp. 389-392 Howarth (1983) MNRAS, vol. 203, p. 301 Calzetti, Kinney & Storchi- Bergmann (1994) ApJ, vol. 429, p. 582

Note that dividing a spectrum by ebmv(val) is equivalent to multiplying the spectrum by ebmv(-val) and has the effect of de-reddening the spectrum. Here are two examples that illustrate several of the spectrum expression features. The first command will calculate a blackbody spectrum of 5000 K and renormalize it to 100 counts in the WFPC2 F555W passband. The output is written to the table rnbb.fits:
sy> calcspec \ >>> "rn(bb(5000),band(wfpc2,f555w),100,counts)" rnbb.fits

The next command creates a power-law spectrum with a slope of -2, normalized to 10­14 ergs/s/cm2/å (f units) in the Johnson V passband, and applies Galactic extinction of E(B­V) = 0.1. The output spectrum is written to the table pl.fits in units of f (fnu):
sy> calcspec \ >>> "rn(pl(5500,-2,fnu),band(v),1.e-14,flam)*ebmv(0.1)" \ >>> pl.fits form=fnu

3.2.4 Form
The form parameter specifies the units of the output spectrum or plot. The synphot package supports the forms listed in Table 3.7. Input and output spectra may be in any of these forms. The output form can differ from that of the input data; conversion is automatic. If you specify an inappropriate form, synphot will display a list of valid forms to choose from.


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Chapter 3: Using Synphot Table 3.7: Forms
FORM fnu flam photnu photlam counts abmag stmag obmag vegamag jy mjy Output Units ergs / s / cm2 / Hz ergs / s / cm2 / å photons / s / cm2 / Hz photons / s / cm2 / å detected counts / s ­2.5 log (FNU) ­ 48.60 ­2.5 log (FLAM) ­ 21.10 ­2.5 log (COUNTS) ­2.5 log (f / f(VEGA)) 10­23 ergs / s / cm2 / Hz 10­26 ergs / s / cm2 / Hz

All spectra are operated on internally in units of photlam.

The following comments should clarify the meanings of the vegamag, abmag, stmag, and counts options; the others are self-evident. The vegamag option, which is defined by setting the magnitude of Vega to zero in all bands, offers a reasonable approximation to many of the conventional photometric systems that use the spectrum of Vega to define magnitude zero in one or more passbands. In broadband photometry, the relevant passband integral is calculated first for the source spectrum and then again for the spectrum of Vega, and the ratio of the two results is converted to a magnitude. vegamag would not be a scientifically meaningful option to use for spectrophotometry. The adopted Vega spectrum can be found in the ASCII file stsdas$lib/synphot/vega.dat, and is defined over a wavelength range of 900 å to 300 m. Oke's AB magnitudes (abmag) are based on a constant flux per unit frequency (see Oke 1974), and the analogous magnitude based on a constant flux density per unit wavelength is the stmag (Space Telescope magnitude) system. The abmag and stmag options are appropriate for either spectrophotometry or photometry. The zeropoint values of 48.60 and 21.10 are chosen for convenience so that Vega has AB and ST magnitudes close to 0 in the Johnson V passband (see Figure 3.1). Because the abmag and stmag systems are defined such that they result in constant magnitudes for spectra having constant flux per unit frequency


Command and Argument Syntax

23

and wavelength, respectively, they will not provide magnitudes on a conventional system, such as UBVRI, without first deriving an appropriate transformation onto the desired standard system.

Because the adopted throughput functions for standard filter systems such as UBVRI are approximations to the complete instrumental passbands that were used to define these photometric systems, synphot results using the UBVRI passbands will only be accurate to a level of about 5% relative to the standard system, even when using form=vegamag. Results are particularly unreliable for the U filter, where the earth's atmosphere determines the blue edge of the passband in the standard ground-based system.

The counts option is used to predict detected count rates. When this form option is selected, tasks such as countrate, calcspec and plspec will calculate the predicted number of detected counts per second per wavelength interval within the passband, and countrate will also report the total number of detected counts integrated over the passband. There are two important things to remember concerning spectra produced in units of counts. First, the number of counts per channel will depend directly on the width (in wavelength space) of the channels in the wavelength grid that is used (see below). All spectra are operated on internally in units of photlam. When output units of counts are requested, the photlam values are multiplied by the collecting area of the telescope and by the width (in Angstroms) of each channel in the wavelength grid. Therefore, in order to accurately predict the number of counts per channel for a spectroscopic instrument, it is necessary to use a wavelength grid that provides a good match to the dispersion properties of the particular instrument mode. The genwave task can be used to produce custom wavelength grids for this purpose, or one of the existing wavelength tables in the STSDAS directory synphot$data can be used (see below). The countrate task automatically uses these tables for STIS, FOS, HRS and NICMOS grism simulations, and for ACS grism/prisms.


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Chapter 3: Using Synphot Figure 3.1: Standard photometric systems illustrated.

Standard photometric systems generally use the spectrum of Vega to define magnitude zero. The spectrophotometric magnitudes AB and ST refer instead to spectra of constant f and f respectively. Magnitude zero in both systems is defined to be the mean flux density of Vega in the Johnson V passband. Thus all three of the spectra shown here produce the same count rate in the Johnson V passband. The pivot wavelength of Johnson V is defined to be the crossing point of the AB = 0 and ST = 0 spectra.

Second, the form counts refers to actual detector counts for the FOC, FOS, HRS, and HSP instruments, while for the WF/PC-1, WFPC2, NICMOS, ACS, and STIS instruments, counts refers to electrons. In order to obtain counts in units of data numbers (DNs) for these instruments, include the keyword "dn" in the obsmode string for WF/PC-1 and NICMOS simulations, either of the keywords "a2d7" or "a2d15" for the WFPC2, and any of the keywords "a2d1", "a2d2", "a2d4", or "a2d8" for STIS (see the modeinfo task for complete lists of HST instrument keywords and their function). These keywords invoke the appropriate electron-to-DN conversion based on the A-to-D gain settings of the instruments. ACS WFC and HRC detectors are always in electrons.


Wavelength Table

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3.3

Wavelength Table
Another parameter used by many synphot tasks is the wavelength table parameter (usually referenced as parameter wavetab). This parameter is used to specify the name of a file containing a list of wavelength values that determine the wavelength grid to be used in the calculations and plotting. The genwave task can be used to generate simple wavelength tables. If the chosen file is an STSDAS or FITS table, it should contain a column named "WAVELENGTH". The wavelength values may be in any of the units listed in Table 3.8 as long as the type of units is specified in the column units table keyword. If the units are not specified in a keyword, Angstroms is assumed. If it is an ASCII text file, the wavelength values must be in the first column and must be in units of Angstroms. In either case, the wavelength values must be in a monotonically increasing or decreasing order.

Since synphot works in single-precision arithmetic, care should be taken that the wavelength intervals specified are not so small as to produce an apparent duplicate entry. This violates the monotonicity constraint and will cause the task to fail.

There is a set of ASCII wavelength tables available for use with the HST
Table 3.8: Wavelength Units
Unit angstroms nanometers microns millimeters centimeters meters in SI 10-10 m 10-9 m 10-6 m 10-3 m 10-2 m 1m Unit hertz kilohertz megahertz gigahertz in SI 1 Hz 103 Hz 106 Hz 109 Hz Unit ev kev mev in SI 1 eV 103 eV 106 eV

spectroscopic instruments in the STSDAS synphot$data directory area. This directory contains separate wavelength tables for each of the STIS, HRS and FOS grating modes and echelle orders, as well as the ACS and NICMOS grisms. The wavelength grid contained in each table covers the range and resolution that is appropriate for each instrument grating as used in a standard observational mode for that instrument.


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Chapter 3: Using Synphot

You may set the which case the task consists of 10000 calculated passband logarithmically over

wavetab parameter to "none" or leave it blank, in will use a default wavelength grid. The default grid points covering the wavelength range where the or spectrum is non-zero. The wavelengths are spaced this range, such that:
min

log 10 ( i ) = log 10 ( where: · i is the ith wavelength value

) + (i ­ 1) â

· = (log10 (max) ­ log10 (min)) / (N ­ 1) · min = wavelength of first non-zero throughput or flux · max = wavelength of last non-zero throughput or flux · N = 10000 If more than one passband or spectrum is specified via the "@filename" syntax for the obsmode or spectrum parameters, the range of the default wavelength grid is computed from the first passband or spectrum in the list. Therefore if the wavelength ranges of the passbands or spectra differ significantly, it is best to specify a suitable wavelength table that covers the complete range of all items in the list.

3.4

Variable Substitution (VZERO)
Several synphot tasks support a method of variable substitution (often referred to as the "VZERO syntax") that can be used to run a series of simulations while varying a parameter over a stepped range.

This can now be accomplished more simply in PyRAF using the Python loop syntax (see Section 2.3.2, "Replacing the "vzero" syntax," on page 10).

If present, the vzero parameter is a list of values that are substituted for variable zero ($0) wherever it appears in the input expression. Each value in the list is substituted in turn. The values must be real numbers. Using vzero is equivalent to placing the input expression several times in a file, with each expression containing one of the values in the list. The list may contain single values or ranges. The endpoints of a range are separated by a dash. An optional step size may follow the range, preceded by the


Reference Data

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letter "x". If the step size is not given, it defaults to 1 or ­1, depending on the order of the endpoints. Table 3.9 gives several examples of valid vzero lists.
Table 3.9: vzero Examples
vzero ".1,.2,.3,.4" ".1-.4x.1" "-1 - -4" "1-9,10-20x2" Resulting list of values 0.1, 0.2, 0.3, 0.4 0.1, 0.2, 0.3, 0.4 ­1, ­2, ­3, ­4 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20 Description A list of values The same list expressed as a range A range with an implicit step size of ­1 A list with more than one range

Variable zero ($0) is used by several synphot tasks. Variables 1 through 9 ($1 - $9) are also used by the fitting tasks.

3.5

Reference Data
Several common parameters are grouped in the refdata parameter set (pset). This pset contains the three parameters shown in Table 3.10
Table 3.10: Parameters in refdata Pset
Parameter area grtbl cmptbl Default Value 45238.93416 "mtab$*_tmg.fits" "mtab$*_tmc.fits" Description Telescope area in cm2 Instrument graph table Instrument component table

The default value for area is the total collecting area of the HST and was computed from the 120 centimeter nominal radius of the HST entrance aperture (the obscuration factor 0.86 due to the secondary mirror is taken into account in the OTA throughput). This value should not be changed unless another telescope is being used. The telescope area is used to convert from counts per square centimeter to total counts. The graph table and component table names specify which tables are to be used by the synphot tasks. The table names may contain the wildcard character "*", in which case the most recent table that matches the name template will be used. The default values for these parameters select the most current graph and component lookup tables installed in the CDBS. The graph table describes all the possible light paths through the telescope and instruments. The component lookup table associates each


28

Chapter 3: Using Synphot

segment of the light paths listed in the graph table with the specific files containing the throughput data for each individual segment. You may use your own versions of the graph and component tables, if you wish. To do this, you would typically copy the default files to your own directory, edit them, and change the names in the refdata parameter set.

3.6

Table formats
Because synphot uses the TABLES package for all its table i/o, all synphot tasks presently support the use of ASCII tables, FITS tables, or STSDAS binary tables (.tab files). However, we are planning to deprecate the .tab format. While it will continue to be supported for at least two more releases or two years (whichever is longer), support will be ended at some point after that. In this manual, we have retained the use of .tab files in some of our examples for historical reasons, but FITS files are strongly recommended as the table format for all current and future synphot use.

3.7

Using EPAR to edit task parameters
The EPAR interface makes it easy to enter task parameters, especially for the tasks that have long and complicated parameter lists. However, any values you enter using EPAR will be saved as new default values for the task. This can produce surprising results when you run the task again, especially for the case of "hidden" parameters for which you are not prompted in interactive mode.

To restore the default task parameters for a task, type unlearn taskname.

3.8

About the Examples in This Manual
Because synphot is a data-driven system, the results obtained by executing a task will change if the underlying data files (throughput files, graph table, etc) have been changed. Therefore, the actual results you


About the Examples in This Manual

29

might obtain by executing the examples may differ from the results printed in the manual. The examples included in this manual are intended only to illustrate the layout and general appearance of the task output. You can check the date on the most recent reference files, and update your local copy of them, from the synphot data download webpage, ftp://ftp.stsci.edu/pub/software/stsdas/refdata/synphot/ .


30

Chapter 3: Using Synphot


CHAPTER 4:

Cookbook
In this chapter. . .
4.1 Bandpasses / 31 4.2 Spectra / 34 4.3 Photometry / 37

This chapter gives step by step examples of how some of the Synphot package tasks are commonly used to answer questions related to HST observing and instrument efficiencies and performance. Detailed descriptions of the tasks used in these examples can be found in Chapter 5.

4.1

Bandpasses
One of the simplest uses of the synphot tasks is to examine the characteristics of instrumental bandpasses. The three main tasks that work specifically with bandpasses are bandpar, calcband, and plband. The bandpar task computes and displays numerical parameters of a bandpass, while calcband and plband calculate and plot, respectively, functions of throughput vs. wavelength for a bandpass. All three tasks are useful for examining individual bandpasses, as well as making comparisons of several bandpasses. The only required user input to both bandpar and plband is the specification of the desired bandpass(es), which is done using the obsmode task parameter (see Section 3.2.2). The calcband task requires the obsmode, as well as the name of an output table in which the results will be stored.
31


32

Chapter 4: Cookbook

For example, let's say you're interested in seeing which of the WFPC2 filters F555W and F569W is the closest match to the Johnson V bandpass. You can make a plot showing the relative throughput vs. wavelength for these three bandpasses using plband as follows:
sy> plband johnson,v sy> plband wfpc2,3,f555w norm+ app+ ltype=dashed sy> plband wfpc2,3,f569w norm+ app+ ltype=dotted

The resulting plot is shown in Figure 4.1. In this example we are plotting the response of the WFPC2 filters when used with CCD chip 3 of the camera. We have used the plband parameter normalize to set the peak transmission of all 3 bandpasses to a value of 1, the parameter append to overplot the WFPC2 bandpasses onto the first plot of the Johnson V bandpass, and the ltype parameter to change the line type for the WFPC2 bandpass plots.
Figure 4.1: Plband Plot of Johnson V and WFPC2 Bandpasses
SYNPHOT.PLBAND

1.25

OBSMODE = johnson,v OBSMODE = wfpc2,3,f555w OBSMODE = wfpc2,3,f569w

1

PASSBAND

.75

.5

.25

0 4500 5000 5500 6000 6500 7000

WAVELENGTH (A)

As you can see, the F569W bandpass is a closer match to Johnson V, especially on the blue edge. However, since the F569W bandpass is narrower than the F555W, it will have a lower overall throughput than the F555W. But how much lower? You can use the bandpar task to find out.


Bandpasses --> bandpar wfpc2,3,f555w photlist=qtlam # OBSMODE wfpc2,3,f555w QTLAM 0.030121

33

--> bandpar wfpc2,3,f569w photlist=qtlam # OBSMODE wfpc2,3,f569w QTLAM 0.023435

Comparing the values of QTLAM, the dimensionless efficiency, for the two bandpasses we see that the F569W has about 78% of the throughput of the F555W. Now let's do a similar experiment in which we wish to find out the relative efficiencies of several of the NICMOS filter bandpasses. First, for convenience, we create a text file called nic_filters.lis, which contains the list of bandpasses (obsmodes) we're interested in (see Figure 4.2).
Figure 4.2: List of NICMOS Filters in File "nic_filters.lis" nicmos,1,f110w nicmos,1,f110m nicmos,1,f160w nicmos,1,f165m nicmos,2,f110w nicmos,2,f160w nicmos,2,f165m nicmos,2,f222m nicmos,3,f110w nicmos,3,f160w nicmos,3,f222m

We then run bandpar, using the @filename notation to specify the name of the file containing our list of obsmodes, and ask for only the QTLAM photometric parameter to be calculated and printed.
sy> bandpar @nic_filters.lis phot=qtlam

Figure 4.3 shows the resulting output from bandpar.


34

Chapter 4: Cookbook Figure 4.3: Bandpar Results for a List of NICMOS Filters # OBSMODE nicmos,1,f110w nicmos,1,f110m nicmos,1,f160w nicmos,1,f165m nicmos,2,f110w nicmos,2,f160w nicmos,2,f165m nicmos,2,f222m nicmos,3,f110w nicmos,3,f160w nicmos,3,f222m QTLAM 0.057824 0.019782 0.048279 0.023963 0.066781 0.053258 0.026823 0.01811 0.060011 0.05143 0.017694

4.2

Spectra
The simplest thing to do with spectra is to just plot them using the plspec task. This is handy, for example, when you're interested in exploring the contents of the available STScI spectral libraries, which are located in the STSDAS crgrid$ directory areas (see Appendix B). Let's say you're interested in making some HST observations of spiral galaxies and you want to see what sort of template galaxy spectra are available for making synphot predictions of observed count rates. A good place to look would be in either the crgridbc95$ (Bruzual-Charlot atlas) or crgridkc96$ (Kinney-Calzetti atlas) directories. To plot one of the spectra, use the plspec task with no obsmode specified (so that the spectrum won't get multiplied by a bandpass), the spectrum parameter set to the name of the table containing the spectral data (see Section 3.2.3), and the output form set to the units of your choice (see Section 3.2.4). The following example plots the spectrum of a type Sb galaxy from the Kinney-Calzetti atlas, in units of flam (ergs/s/cm2/å).
sy> plspec "" crgridkc96$sb_template.fits flam

How does this compare to the spectrum of a typical elliptical galaxy? You can find out by overplotting:
sy> plspec "" crgridkc96$elliptical_template.fits flam \ >>> app+ ltype=dotted

This uses the append parameter to overplot the spectra and the ltype parameter to change the line type of the second spectrum. The result is shown in Figure 4.4.


Spectra Figure 4.4: Plotting Spectra with plspec
SYNPHOT.PLSPEC 5.00E-14 REFSPEC = crgridkc96$sb_template REFSPEC = crgridkc96$elliptical_template 4.00E-14

35

FLAM (ergs cm-2 s-1 A-1)

3.00E-14

2.00E-14

1.00E-14

0 2000 4000 6000 8000 WAVELENGTH (A)

Well, that's interesting, but what we'd really like to know is what will the spectrum of one of these targets look like when observed with an HST spectroscopic instrument? To create a predicted observed spectrum we could simply rerun plspec (or calcspec), this time giving it an obsmode corresponding to one of the HST instrumental modes. However, because the detected count rate per channel in a spectroscopic mode depends directly on the width of each channel in wavelength space, we would have to be careful to first construct a wavelength set that matches the dispersion characteristics of the instrumental mode(s) we're interested in. It is much easier, however, to just use the countrate task, which automatically uses a library of existing wavelength sets appropriate for each HST spectroscopic mode. The parameters for the countrate task are a little bit different than those of other synphot tasks, in that there is no obsmode parameter. Instead, the instrument mode is specified via a set of individual parameters for the instrument, detector, filter or grating, and aperture or slit. Let's say we want to simulate a STIS observation of the Sb-type galaxy we looked at earlier with plspec, using the STIS CCD detector, its low-resolution G430L grating, and the 50" x 0.5" entrance slit. We'll also assume that the galaxy


36

Chapter 4: Cookbook

we want to observe has a V magnitude (within the slit area) of 18 and we'll try an exposure time of 500 seconds. Figure 4.5 shows how to set the countrate task parameters for this simulation.
Figure 4.5: countrate Parameters for STIS CCD Observation spectrum magnitude instrument detector spec_elem aperture cenwave exptime reddening redlaw output form magform wavecat refwave verbose flux_tot flux_ref refdata = = = = = = = = = = = = = = = = = = = "crgridkc96$sb_template.fits" "18 v" stis ccd g430l 52x0.5 INDEF 500. 0.0 gal1 sb_stis_g430l.fits counts vegamag synphot$data/wavecat.dat INDEF yes INDEF INDEF ""

You can then use plspec, or any STSDAS plotting task that can read tables, to plot the observed spectrum stored in the file "sb_stis_g430l.fits". Figure 4.6 shows the spectrum as plotted using the STSDAS sgraph task.
sy> sgraph "sb_stis_g430l wavelength flux"


Photometry Figure 4.6: Predicted STIS CCD Spectrum Produced by countrate

37

NOAO/IRAF V2.11EXPORT bushouse@marvin.stsci.edu Wed 15:05:17 28-Jan-98 marvin.stsci.edu!/home/bushouse/iraf/sb_stis_g430l

300

flux [counts]

200

100

0 3000 3500 4000 4500 5000 5500 wavelength [angstroms]

4.3

Photometry
The calcphot task is very useful for making quick estimates of the total number of counts that will be detected in an HST imaging observation of a particular source, normalized to an aperture of some (instrument-dependent) size. For example, let's again use that spectrum of an Sb galaxy to calculate the total counts that would be detected when observed with the WFPC2, in chip 3, using filter F439W (the WFPC2 analog to Johnson B).
sy> calcphot wfpc2,3,f439w \ >>> "rn(crgridkc96$sb_template.fits,band(v),18,vegamag)" \ >>> counts

Here we've used the rn (renormalize) function in the spectrum parameter to renormalize the Sb galaxy spectrum to a V-band magnitude of 18. We've also asked for the answer to be computed in units of counts, which for the WFPC2 is equivalent to electrons. It's also possible to get the answer in units of DNs (data numbers). To do this for the WFPC2, we


38

Chapter 4: Cookbook

would need to include the additional keyword "a2d7" in the obsmode string (i.e., "wfpc2,3,f439w,a2d7"), which applies the appropriate electron-to-DN conversion ratio for the WFPC2 gain setting of 7. The calcphot results are shown in Figure 4.7.
Figure 4.7: Calcphot Results for a WFPC2 F439W Observation Mode = band(wfpc2,3,f439w) Pivot Equiv Gaussian Wavelength FWHM 4311.664 476.1779 band(wfpc2,3,f439w) Spectrum: rn(crgridkc96$sb_template.fits,band(v),18,vegamag) VZERO (COUNTS s^-1 hstarea^-1) 0. 42.3929

So this galaxy produces a total countrate of 42.4 e­/sec, which means we'll need an exposure time of at least 235 seconds in order to approach an accuracy of 1% in measuring its total light. Another question an HST observer might ask is "How faint can I go in an exposure time of t seconds if I want x percent photometry?" To answer this, you could either run calcphot over and over again the way we just did in the last example, picking different renormalization magnitudes for your source until you get the countrate that corresponds to your desired S/N, or you could run the equivalent simulation "backwards". For example, if you're interested in observing red stars with the NICMOS, you can pick a suitable stellar spectrum from the crgridbpgs$ area (Bruzual-Persson-Gunn-Stryker atlas), and then run calcphot as follows.
sy> calcphot h \ >>>"rn(crgridbpgs$bpgs_147.fits,band(nicmos,2,f160w), 10,counts)"\ >>> vegamag

Here we've picked star number 147 from the BPGS atlas, which is a K5 giant. We want to observe with NICMOS camera 2 and the F160W filter and want to see how faint we can go in 100 seconds and get 3% photometry. To obtain this measurement accuracy we need a total of 1000 electrons detected from the source, so for an exposure time of 100 seconds we need a countrate of 10 e­/sec. We've again used the rn function to renormalize the spectrum, but this time we've renormalized it to our desired countrate of 10 in the "nicmos,2,f160w" band. Once it's been renormalized, calcphot then computes the H magnitude of the spectrum (in units of vegamag, since the JHK filter system uses Vega as its zeropoint). The results from calcphot are shown in Figure 4.8, where we see that we can reach an H magnitude of 21.4.


Photometry Figure 4.8: Calcphot Results for a NICMOS F160W Observation Mode = band(h) Pivot Equiv Gaussian Wavelength FWHM 16448. 2040.596 band(h) Spectrum: rn(crgridbpgs$bpgs_147.fits,band(nicmos,2,f160w),10,counts) VZERO VEGAMAG Mode: band(h) 0. 21.3681

39

The calcphot task is also useful for making photometric measurements of existing spectra, either in HST instrumental bands or standard ground-based filter systems. For example, let's say you'd like to demonstrate for some students the importance of the 4000 å break on the U-B colors of redshifted galaxy spectra. First, you might want to produce a plot showing the U and B bandpasses relative to some redshifted spectra. The plspec and plband commands shown in Figure 4.9 will produce the plot shown in Figure 4.10. Note that the bandpass plots are multiplied by a scale factor to place them in the same range of data values as the spectra. The commands below use the iraf cl syntax for specifying task parameters without invoking the task. This is sometimes useful for setting plotting ranges, as in this case.

In PyRAF, you must use the syntax iraf.plspec.left = 3000 to specify task parameters in this way.

Figure 4.9: Commands for Plotting Redshifted Spectra and UB Bands plspec.top = 6e-14 plspec.left = 3000 plspec.right= 6500 plspec "" "z(crgridkc96$elliptical_template.fits,0.0)" plspec "" "z(crgridkc96$elliptical_template.fits,0.2)" plspec "" "z(crgridkc96$elliptical_template.fits,0.3)" plspec "" "z(crgridkc96$elliptical_template.fits,0.4)" plspec "" "z(crgridkc96$elliptical_template.fits,0.8)" plband "band(u)*3.e-14" app+ plband "band(b)*3.e-14" app+

flam flam flam flam flam

app+ app+ app+ app+


40

Chapter 4: Cookbook Figure 4.10: Plots of Redshifted Spectra and UB Bandpasses

Now we run calcphot, having it compute the U-B colors of these spectra. We'll use the synphot expression variable $0 for the redshift value in the z function, and then specify the range of redshifts that we want in the task parameter vzero. This tells calcphot to automatically run the calculation several times, each time substituting a different value for the redshift. The complete calcphot command and results are shown in Figure 4.11.
Figure 4.11: Using calcphot to Compute U-B Colors of Redshifted Spectra --> calcphot "band(u)-band(b)" "z(crgridkc96$elliptical_template.fits,$0)" vegamag vzero="0-0.8x0.2" Mode = band(u) - band(b) Pivot Equiv Gaussian Wavelength FWHM 3646.236 484.6001 band(u) 4433.497 831.1038 band(b) Spectrum: z(crgridkc96$elliptical_template.fits,$0) VZERO VEGAMAG(band(u)) - VEGAMAG(band(b)) 0. 0.645421 0.2 0.90348 0.4 1.022621 0.6 -0.10024 0.8 -0.55384


CHAPTER 5:

Task Descriptions
In this chapter. . .
5.1 Bandpar 5.2 Calcband 5.3 Calcphot 5.4 Calcspec 5.5 Countrate 5.6 Fitband 5.7 Fitspec 5.8 Fitgrid 5.9 Genwave 5.10 Grafcheck 5.11 Graflist 5.12 Grafpath 5.13 Imspec 5.14 Mkthru 5.15 Modeinfo 5.16 Obsmode 5.17 Plband 5.18 Plspec 5.19 Plratio 5.20 Pltrans 5.21 Refdata / 5.22 Showfiles / 5.23 Thermback / / 42 / 44 / 46 / 50 / 54 / 59 / 63 / 68 / 72 / 73 / 74 / 75 / 76 / 78 / 80 / 81 / 82 / 85 / 94 / 98 101 102 103

This chapter describes in detail how each task in the synphot package operates and what parameters each task uses.

41


42

Chapter 5: Task Descriptions

5.1

Bandpar
The bandpar task computes various photometric parameters, as shown in Table 5.1, for a selected passband. The computed photometric parameters can be saved to a FITS or STSDAS table.
Table 5.1: Bandpar Photometric Parameters
Parameter uresp pivwv bandw fwhm wpeak tpeak avgwv qtlam equvw rectw emflx tlambda refwave Description Unit response; flux (in flam) that produces 1 count/second in the passband Pivot wavelength of passband RMS band width Full width half maximum of an equivalent gaussian Wavelength at peak throughput Peak throughput of passband Passband average wavelength Dimensionless efficiency Equivalent width of passband Rectangular width of passband Equivalent monochromatic flux Throughput at reference wavelength Reference wavelength for tlambda Formula ( hc ) / ( area P d ) ( P d ) / ( P d / ) P ln ( / ) d / ------------------------------------------------- P d / 8 ln2 â bandw where ( P = max ( ( P ) ) max ( P ) P d ------------------- P d ( P d ) / P d ( P d ) / max ( P ) tpeak uresp rectw --------------------- tlambda P ( refwave ) ( P d ) / ( P d )
2

In the table above, P is the (dimensionless) passband throughput as a function of wavelength, area is the telescope collecting area, h and c are the usual physical constants, and is the mean wavelength of the passband defined in Schneider, Gunn, and Hoessel (1983) as: P ln ( ) d / ----------------------------------- = exp P d / This rather unusual definition has the property that the correspondingly defined mean frequency is just c / . Unless specified by the user, the refer-


Bandpar

43

ence wavelength (refwave) used in the computation of tlambda and emflx is set to the average wavelength of the passband (avgwav). The bandpar task parameters are shown in Figure 5.1, below.
Figure 5.1: Bandpar Parameters obsmode (output (photlist (refwave (wavetab (refdata = = = = = = Instrument observation mode(s) Output table name Photometric parameters to calculate Wavelength used in computing EMFLX Wavelength table name Reference data

"none") "all") INDEF) "") "")

The obsmode parameter may be any valid string of HST instrument mode keywords, passband functions--such as gauss, box, or poly--or the name of a table (text or FITS or STSDAS binary) containing wavelength and throughput data. A series of obsmode strings may be processed by putting them in a text file, one per line, and setting obsmode=@filename. See Section 3.2.2 for more details about all of the available specifications for obsmode, and "Filename specifications" on page 19 for important side effects of using the @filename syntax. If the output parameter is null or set to "none", no output table will be created. However, output will always be sent to STDOUT (terminal). The output table will contain columns for each of the photometric quantities specified in the photlist parameter (see below). The output table will also contain the table header keywords GRFTABLE, CMPTABLE, and APERAREA as a record of the settings used in the computations. If more than one obsmode is specified using an input list file, then the output table will have separate rows containing the parameters computed for each passband. The photlist parameter contains a comma separated list of the names of the photometric parameters to be printed. The value "all" prints all of them. Placing a "~" in front of the list causes all of the parameters except those in the list to be printed. The two auxiliary parameters refwave and tlambda are printed by default if emflx is printed, and not printed by default if emflx is not printed. The refwave parameter specifies the reference wavelength to be used in the computation of emflx. If this parameter is set to INDEF, the average wavelength (avgwv) will be calculated as shown in Table 5.1 and used as the reference wavelength. The units of a user-specified reference wavelength must be Angstroms. Null values for the wavetab and refdata parameters will cause the task to use a default wavelength grid (see Section 3.3) and the default reference data for the HST observatory (see Section 3.5).


44

Chapter 5: Task Descriptions

5.1.1 Examples
The following command computes all available photometric parameters for the passband of the ACS Solar Blind Channel (SBC) with longpass filter f150lp. The output is not saved in a table.
sy> bandpar acs,sbc,f150lp

The next example calculates only the pivot wavelength and the rms bandwidth for each of the Johnson UBV passbands, and saves the results in the table ubv.fits. The input file ubv.lis contains the lines:
band(u) band(b) band(v) sy> bandpar @ubv.lis output=ubv.fits phot=pivwv,bandw

The last example calculates the photometric parameters for the WFPC2 detector 2 and F439W filter, setting the reference wavelength to 4300 å. The reference wavelength is not printed.
sy> bandpar wfpc2,2,f439w refwave=4300 phot=~refwave

5.2

Calcband
The calcband task will calculate a passband by combining existing passbands, certain functional forms such as a Gaussian or a rectangular window, or throughput data read in from a file. These data can optionally be multiplied by a Legendre polynomial to modify the passband shape. The task takes any valid obsmode command string as input and produces a FITS or STSDAS table with two columns of data, called WAVELENGTH and THROUGHPUT, as its output. The task parameters are shown in Figure 5.2, below.
Figure 5.2: Calcband Parameters obsmode output (wavetab (refdata = = =) =) Instrument observation mode passband Output table name Wavelength table name Reference data

The obsmode parameter may be any valid string of HST instrument modes, passband functions--such as gauss, box, or poly--or the name of a file (FITS file, STSDAS table or plain ASCII text) containing columns of throughput data. A series of obsmode strings may be processed by storing them in a text file, one per line, and setting obsmode=@filename. See Section 3.2.2 for more details about all of


Calcband

45

the available specifications for obsmode, and "Filename specifications" on page 19 for important side effects of using the @filename syntax. If more than one passband is specified via a list file, then a separate "THROUGHPUTn" column is created in the output table for each of the n passbands listed in the file. The output table also contains the following header keywords (listed in Table 5.2), many of which are the same photometric quantities computed by the bandpar task. The header can be read using thedit or catfits.
Table 5.2: Calcband Output Keywords
Keyword grftable cmptable expr aperarea zeropt uresp pivwv bandw tpeak equvw rectw emflx Description Name of the instrument graph table Name of the component lookup table Value of the obsmode parameter Telescope collecting area, in cm2, used to compute uresp Photometric zeropoint of the STMAG system Unit response; flux (in flam) that produces 1 count/second in the passband Pivot wavelength of passband RMS band width Peak throughput of passband Equivalent width of passband Rectangular width of passband Equivalent monochromatic flux ( hc ) / ( aperarea P d ) ( P d ) / ( P d / ) P ln ( / ) d / ------------------------------------------------- P d / max ( P ) P d ( P d ) / max ( P ) tpeak uresp rectw --------------------- tlambda
2

Formula

If more than one passband is specified via a list file, the last eight header keywords are repeated, once for each passband, with the names EXPRn, URESPn, PIVWVn, BANDWn, TPEAKn, EQUVWn, RECTWn, and EMFLXn for the nth passband. Null values for the wavetab and refdata parameters will cause the task to use a default wavelength grid (See "Wavelength Table" on page 25.) and the default reference data for the HST observatory (see Section 3.5). The default wavelength grid covers the wavelength range where the passband throughput is non-zero. Wavelengths are spaced logarithmically over this range. If there is more than one passband specified, the range of the default grid is computed based on the first passband. Therefore, if the


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Chapter 5: Task Descriptions

wavelength ranges of the passbands differ significantly, a suitable wavelength table that covers the range of all the passbands should be constructed using the genwave task, and supplied as input via the wavetab parameter.

5.2.1 Examples
The following command shows how to calculate a Gaussian centered at 4800 å, multiply it by a first-order Legendre polynomial (which, by the way, produces a close match to the Johnson V passband), and write the results to a table called gauss_tilt.fits.
sy> calcband "tilt(gauss(4800,1300),10)" gauss_tilt.fits

The next example shows how to evaluate the total telescope plus instrumental throughput for an HST observation using the STIS FUVMAMA detector, and the e140h grating. The resulting throughput data are stored in the table stis_thpt.fits.
sy> calcband stis,e140h,fuvmama stis_thpt.fits

5.3

Calcphot
The calcphot task is useful for calculating the integrated counts or flux in a given passband for a particular spectrum. Passband information, such as pivot wavelength, FWHM, and rms bandwidth, can also be calculated. The output may be saved to a FITS or STSDAS table, if desired. Task parameters include the observation mode and spectrum parameters that were discussed for the calcband and calcspec tasks, and discussed in detail in Section 3.2.2 and Section 3.2.3. The full list of task parameters is shown in Figure 5.3.
Figure 5.3: obsmode = spectrum = form = (func = (vzero = (output = (append = (wavetab = (result = (refdata = Calcphot Parameters Instrument observation mode Synthetic spectrum to calculate photlam Form for output data effstim) Function of output data ) List of values for variable zero none) Output table name no) Append to existing table? ) Wavelength table name ) Result of synphot calculation for form ) Reference data

The form parameter may be any of the accepted types (fnu, flam, photnu, photlam, abmag, stmag, counts, obmag, vegamag, jy, or


Calcphot

47

mjy). By default, the task calculates and reports the values of the pivot wavelength and FWHM in addition to the quantity chosen by form. The func parameter determines what output function is computed. The default value (effstim) calculates the predicted count rate or flux. This is the function most users will use. The other functions compute various functions of the product of the passband throughput and the spectrum. The spectrum is first converted into the units specified by the form parameter before computing the function, so results will depend on whether the form has frequency or wavelength units. The sole exception is efflam, which is always equivalent to avglam computed in count units. The efflam form is included for compatibility with a previous version of calcphot.
Table 5.3: Functions Suppor ted by Calcphot
Form Description Formula f P d ------------------------- f P d f P ln ( ) d / = exp ----------------------------------------- f P / f P d ---------------------------- f P d hc f P d --------------------------------- P d 8 ln2 â rmslam f P ln ( / ) d / ------------------------------------------------------- f P d /
2 2

avglam

Average wavelength

barlam

Mean log ("bar") wavelength

efflam

Effective wavelength

effstim fwhmlam rmslam

Effective stimulus [flam] FWHM bandwidth RMS bandwidth

In the table above, P is the (dimensionless) passband throughput, f is the source flux distribution, and is the mean wavelength of the passband as defined in Schneider, Gunn, and Hoessel (1983). If desired, the spectrum expression may contain variable zero ($0), so that the photometric calculations are repeated over the series of values specified by the vzero parameter. See the examples section below for details on how this can be used, and see Section 3.4, "Variable Substitution (VZERO)," on page 26 for more details. The result parameter is an output parameter and contains the result of the requested photometric calculation. This can be the observed flux of the synthetic spectrum in the selected observation mode, or it can be a passband parameter as specified by the form parameter. This parameter contains the result of the last calculation performed, so if several spectra or


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Chapter 5: Task Descriptions

modes are given via a list file, or the calculation is repeated over a series of vzero values, then only the result of the last calculation is saved. The results of calculations may be saved in a FITS or STSDAS table, if desired, via the output parameter. This table contains the columns of information described in Table 5.4.
Table 5.4: Calcphot Output Table Columns
Column COUNTRATE FORM OBSMODE TARGETID Contents Result of photometric calculation in units of form or FUNC Units of COUNTRATE Instrument observing mode Synthetic spectrum specification

There is one table row for each calculation performed. This table can be used as input to the plspec task and other tasks using the pfile (photometry file) parameter. If form is set to counts or obmag, then the value of COUNTRATE as stored in this table is normalized to the telescope area. If calculating one of the passband parameters listed in Table 5.1, the name of the first column of the output table is the name of that parameter. Null values for the wavetab and refdata parameters will cause the task to use a default wavelength grid (see Section 3.2.2) and the default reference data for the HST observatory (see Section 3.5). The default wavelength set covers the range where the obsmode and spectrum are non-zero. If there is more than one obsmode and spectrum, the range is computed based on the first pair. If the wavelength ranges of the obsmodes and spectra differ significantly, a suitable wavelength table should be specified explicitly.

5.3.1 Examples
The first example (Figure 5.4) uses calcphot to calculate the integrated flux (in DNs per second) of a 5000 K blackbody in the passband defined by the WFC detector 2 and F555W filter. The blackbody spectrum is renormalized to have a V magnitude of 18.6. Specifying the generic instrument name "wfpc" in the obsmode string results in the use of the default WFC detector number 2. By default, the pivot wavelength and FWHM of the specified passband are also calculated.


Calcphot Figure 5.4: Sample Calcphot Run sy> calcphot wfpc,f555w,dn \ >>> "rn(bb(5000),band(v),18.6,vegamag)" counts Mode = band(wfpc,f555w,dn) Pivot Equiv Gaussian Wavelength FWHM 5467.652 1200.957 band(wfpc,f555w,dn) Spectrum: rn(bb(5000),band(v),18.6,vegamag) VZERO (COUNTS s^-1 hstarea^-1) 0. 55.41071

49

The next example (Figure 5.5) computes the flux of the same blackbody spectrum through the WFPC2 and its F439W and F555W filters (similar to Johnson B and V), and finds the color difference (in instrumental magnitudes) between the two. The calculation is repeated for values of E(B­V) of 0.0, 0.25, and 0.5 applied to the blackbody spectrum.
Figure 5.5: Second Sample Calcphot Run sy> calcphot "band(wfpc2,4,f439w)-band(wfpc2,4,f555w)" \ >>> "bb(5000)*ebmv($0)" obmag vzero="0,0.25,0.5" Mode = band(wfpc2,4,f439w) - band(wfpc2,4,f555w) Pivot Equiv Gaussian Wavelength FWHM 4311.846 476.3737 band(wfpc2,4,f439w) 5442.215 1229.98 band(wfpc2,4,f555w) Spectrum: bb(5000)*ebmv($0) VZERO OBMAG(band(wfpc2,4,f439w))-OBMAG(band(wfpc2,4,f555w)) 0. 2.535146 0.25 2.77968 0.5 3.03

As we might have expected, the change in the F439W-F555W color of the spectrum is about 0.25 mag for every 0.25 mag change in E(B­V)! For a final example, we'll demonstrate the use of the ACS-specific parameterized keyword aper#. This keyword was implemented to permit the calculation of source counts as a function of photometric aperture. It simulates the performance of aperture photometry on the model spectrum. The keyword allows the user to specify the radius of the photometric aperture in arcseconds. This feature is particularly useful for near-IR filters where the aperture correction can be dependent on the spectral energy distribution of the object First we calculate the integrated flux (in counts per second) of a K0V star in the passband defined by the Wide Field Channel and the f850lp filter. The star spectrum is renormalized to have a V magnitude of 24.


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From the command line within synphot we type the usual syntax (common to all instruments):
sy> calcphot acs,wfc1,f850lp "rn(icat \ (k93models,5250,0.0,5.0),band(v),24,vegamag)" \ counts func=effstim

In return we obtain the total number of counts for an infinitely large region. In fact, in our example we did not specify or ask for a special aperture.
Mode = band(acs,wfc1,f850lp) Pivot Wavelength 9054.795 Spectrum: amag) VZERO 0. Equiv Gaussian FWHM 1270.317 band(acs,wfc1,f850lp) rn(icat(k93models,5250,0.0,5.0),band(v),24,veg(COUNTS s^-1 hstarea^-1) 3.451657

The next example is to calculate the source counts that are in a user's specified aperture. We choose a 0.1 arcsec radius aperture.
sy> calcphot "acs,wfc1,f850lp,aper#0.1"\ "rn(icat(k93models,5250,0.0,5.0),band(v),24,vegamag)"| counts func=effstim

In output we obtain:
Mode = band(acs,wfc1,f850lp,aper#0.1) Pivot Equiv Gaussian Wavelength FWHM 8959.136 1158.454 band(acs,wfc1,f850lp,aper#0.1) Spectrum:rn(icat(k93models,5250,0.0,5.0),band(v),24,vegamag) VZERO (COUNTS s^-1 hstarea^-1) 0. 1.709906

As expected, the amount of flux within a 0.1" radius aperture is significantly smaller. Because the definition of pivot wavelength depends on throughput (see Table 5.1), the pivot wavelength, and the FWHM of the bandpass centered on it, also change slightly.

5.4

Calcspec
The calcspec task will create a synthetic spectrum by combining existing models, such as a blackbody or power-law, as well as spectra read from a file. The spectral data can be manipulated in various ways, including multiplying by a passband, scaling by constants, adding or removing extinction, and normalizing to an arbitrary value in a specified passband. Unit conversion is performed automatically when adding or subtracting spectra that have different forms (units). Spectra cannot be multiplied


Calcspec

51

together, but they can be multiplied by arbitrary (unitless) constants and passbands. The resulting spectral data are written to a FITS or STSDAS table containing columns of wavelength and flux. The wavelength data will be in units of Angstroms and the flux data will be in the unit system specified by the task parameter form. If the output form is chosen to be either counts or obmag, then the flux data written to the output table are scaled by the telescope area. The columns in the output table are labeled WAVELENGTH and FLUX. The task parameters are shown in Figure 5.6 below.
Figure 5.6: Calcspec Parameters spectrum output (form (vzero (wavetab (refdata = = = = = = Spectrum to calculate Output table name Desired form of output spectrum List of values for variable zero Wavelength table name Reference data

photlam) "") "") "")

The spectrum parameter can be a string of any valid commands and arguments that specify the spectrum to be synthesized. Multiple spectrum commands may be placed in a text file, one per line, and specified as spectrum=@filename. See Section 3.2.3 for a detailed list and description of all the available spectrum commands, and "Filename specifications" on page 19 for important side effects of using the @filename syntax. If more than one spectrum expression is specified via a text file, then a separate "FLUXn" column is created in the output table for each spectrum. The output table contains the header keywords GRFTABLE, CMPTABLE, and EXPR, which are the names of the instrument graph table, the component lookup table, and the spectrum parameter string. If more than one spectrum is specified via a file, each one will be listed as a separate header keyword, with the name EXPRn. The vzero parameter contains a list of values that are substituted for variable zero ($0) wherever it appears in the spectrum expression. See Section 3.4, "Variable Substitution (VZERO)," on page 26 for a discussion of variable substitution. Null values for the wavetab and refdata parameters will cause the task to use a default wavelength grid (See "Wavelength Table" on page 25.) and the default reference data for the HST observatory (see Section 3.5). The default wavelength grid covers the wavelength range where the spectrum is non-zero. Wavelengths are spaced logarithmically over this range. If there is more than one spectrum specified, the range of the default wavelength grid is computed based on the first spectrum. Therefore, if the


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wavelength ranges of the spectra differ significantly, a suitable wavelength table that covers the desired range of all the spectra should be created using the genwave task and supplied as input via the wavetab parameter.

5.4.1 Examples
The following example synthesizes a 5000 K blackbody spectrum and renormalizes it so that it produces an integrated flux of 100 counts (DN) per second in the WFPC2 F555W passband. The spectral data, in units of flam, are written to the table rnbb.fits.
sy> calcspec \ >>> "rn(bb(5000),band(wfpc2,f555w,a2d7),100,counts)" \ >>> rnbb.fits form=flam

The next example simulates an observation of the flux calibration standard star G191-B2B using the FOS blue-side detector with the 1.0" aperture and the G190H grating. The spectral data for G191-B2B are in the table crcalspec$g191b2b_stis_001.fits, in units of flam. First, in order to simulate the true count rate per diode as accurately as possible, we must either create a wavelength table, using the genwave task, that approximates the dispersion relation for the G190H grating, or use an existing wavelength table for this grating that is available in the STSDAS synphot$data directory called fos_blue_g190h.dat. To make our own table we use genwave as follows:
sy> genwave g190h.fits minw=1573.0 maxw=2330.0 dwave=1.47

where the dispersion parameters have been obtained from the FOS Instrument Handbook. Now we run calcspec, multiplying the spectrum of G191-B2B by the desired FOS observation mode. The simulated spectrum, in counts per second per diode, is written to the table g191_fos.fits.
sy> calcspec \ "crcalspec$g191b2b_stis_001.fits*band(fos,blue,1.0,g190h)" \ g191_fos.fits form=counts wavetab=g190h.fits

The resulting count rate spectrum is shown in Figure 5.7. You can create a similar plot by using the plspec command to display the resulting table (plspec "" g191_fos.fits form=counts ). If we wanted to use the wavelength table from the data directory, we would specify "wavetab=synphot$data/fos_blue_g190h.dat" on the command line.


Calcspec Figure 5.7: FOS Count Rate Spectrum of G191-B2B

53

For a final example, let's suppose a star observed with the WFPC2 and filter F439W produces 1200 counts (DNs) per second. What would its spectrum be for various blackbody temperatures ranging from 5000 to 20000 K, in steps of 1000 K?
sy> calcspec \ >>> "rn(bb($0),band(wfpc2,f439w,a2d7),1200,counts)" \ >>> bbody.fits form=flam vzero="5e3-20e3x1e3"

The resulting spectra, in units of flam, are stored in the output table bbody.fits. Some of the spectra are shown in Figure 5.8.You can generate a similar plot by using the plspec command with equivalent parameters (plspec "" \ "rn(bb($0),band(wfpc2,f439w,a2d7),1200,counts)"\ form=flam vzero="5e3-20e3x1e3" right=8000\ left=2000) .


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Chapter 5: Task Descriptions Figure 5.8: WFPC2 Blackbody Spectra

5.5

Countrate
The countrate task is similar to the calcspec and calcphot tasks in that, for a given input spectrum and HST observing mode, it will compute a countrate spectrum, as well as the total counts integrated over the passband defined by the observing mode. There are, however, two unique features to this task. First, the input parameters were originally structured to mimic what is contained in the exposure logsheets found in HST observing proposals under the RPS2 proposal entry system in use at the time. (Since then, the Astronomer's Proposal Tool (APT), which has a different user interface, has become the standard tool for Phase 2 proposals; so this feature is no longer especially useful.) Secondly, for the spectroscopic instruments, it will automatically search for and use a wavelength table from the STSDAS synphot$data directory that is appropriate for the selected instrumental dispersion mode. This remains extremely useful, and the countrate task therefore remains ideally suited to predicting exposure


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times when writing HST proposals. countrate is the underlying engine for the Exposure Time Calculators (ETCs) that are provided by STScI for use in proposal preparation. Figure 5.9 is a list of the task parameters.
Figure 5.9: Countrate Task Parameters
spectrum = Spectrum to calculate magnitude = Magnitude and passband of spectrum instrument = Science instrument (detector = " ") Detector used (spec_elem = " ") Spectral elements used (aperture = " ") Aperture / field of view (cenwave = INDEF) Central wavelength (HRS and STIS only) (exptime = 1.) Exposure time in seconds (reddening = 0.) Interstellar reddening E(B-V) (redlaw = "gal1") Reddening law used (gal1|gal2|gal3|smc|lmc|xgal (output = "none") Output table name (form = "counts") Form for output data (magform = "vegamag") Form for magnitude (wavecat = "synphot$data/wavecat.dat") Catalog of wavelength tables (refwave = INDEF) Reference wavelength (verbose = yes) Print results to STDOUT ? (flux_tot = INDEF) Estimated total flux (output) (flux_ref = INDEF) Estimated flux at reference wavelength (output) (refdata = "") Reference data

Unlike other synphot tasks in which the observing mode is specified via the single parameter obsmode, the countrate task uses separate instrument, detector, spec_elem, and aperture parameters to specify the observing mode. The instrument parameter specifies one of the HST instruments: acs,fgs, foc, fos, hrs, hsp, nicmos, stis, wfpc, or wfpc2. If you set the instrument parameter to hrs or stis, you should also specify a value for cenwave, the central wavelength of the spectrum (see below). The detector parameter specifies the name of the desired detector, if there is more than one available for the chosen instrument. The spec_elem parameter specifies the name of spectral elements, such as filters or gratings. Finally, the aperture parameter specifies the name of the instrument aperture, if there is more than one available for the chosen instrument. The instrument parameter must always be specified, but one or more of the detector, spec_elem, and aperture parameters may be left blank, depending on their applicability to a given instrument. A standard obsmode string is constructed internally by the task by concatenating the instrument, detector, spec_elem, and aperture parameter strings. Therefore, if you want to include an extra mode keyword in the desired instrument mode, you can do so by including the keyword along with any others that are given for the four parameters mentioned above. For example, if you want to include the effects of contamination on MJD 50477 in a WFPC2 simulation using the f300w filter, you could specify "spec_elem=f300w,cont#50477".


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The cenwave parameter specifies the central wavelength for the simulated observation, in Angstroms; the output spectrum will be centered at this wavelength. If set to INDEF, the output spectrum will contain the entire wavelength range covered by the chosen observation mode. This parameter only affects HRS and STIS instrument modes, because they are the only instruments for which the detector cannot cover the entire wavelength range of an observation. This parameter is ignored for all other instrument modes. The target spectrum is specified as any valid synphot spectrum expression given in the spectrum parameter, to be renormalized to the magnitude given in the magnitude parameter using the form of the magform parameter. The crcalspec$ and crgrid$ directories contain tables of HST flux calibration star spectra and various spectral atlases (both models and observational data) that can be used as source spectra (see Appendix A:On-Line Catalogs and Spectral Atlases), or you can use a synthetic spectrum function to generate a spectrum at run-time. The spectrum parameter recognizes all of the valid functional forms that can be specified via to the spectrum parameter in other synphot tasks. The magnitude parameter is used in conjunction with spectrum to renormalize the spectrum to a chosen magnitude. This is done by specifying the desired integrated broadband magnitude, in units of magform, for the spectrum in one of the standard UBVRI passbands. The syntax used to specify magnitude is a two-word string consisting of the desired magnitude value, followed by the name of the desired passband, e.g., "magnitude=15.6 V." The reddening parameter may be used to add or remove the effects of interstellar reddening on the input spectrum and is specified in units of E(B­V). It provides the same functionality as the ebmvx function in the spectrum interpreter of other synphot tasks. The redlaw parameter gives the reddening law to use in the ebmvx function. The default value, gal1, is Seaton's law and the same as by the ebmv function. The exptime parameter is used to specify the desired exposure time, in seconds, to be applied in the calculation of the integrated counts and the countrate spectrum. Therefore, if exptime=1, the result will be a true count rate (counts per second), whereas if exptime > 1, the result will be the total counts accumulated in that time. The output table produced by countrate is a FITS or STSDAS table containing columns of WAVELENGTH and FLUX, in units of Angstroms and form, respectively. This table will also contain the header keywords GRFTABLE, CMPTABLE, OBSMODE, SPECTRUM, and EXPTIME, corresponding to the values of the related task parameters. The output parameter may be set to either "none" or a null string (i.e., " "), in which case no output table will be created, but the integrated counts within the passband will still be printed to STDOUT (terminal).


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In addition to computing the total counts integrated over the chosen instrument passband, it is possible to compute the number of counts at a particular reference wavelength through the use of the refwave parameter. If the chosen instrument is a spectrograph (FOS, HRS, or STIS), the task will compute the counts in the pixel containing the reference wavelength. If the chosen instrument is not a spectrograph, the task will compute the counts per Angstrom at the chosen reference wavelength. If the verbose parameter is set to "yes", then the results of the total counts and counts at the reference wavelength calculations will be written to STDOUT (terminal). In addition, these two quantities are also written to the output parameters flux_tot and flux_ref.

5.5.1 Examples
This example computes the result of a 1800 second observation of Feige 110, using the HRS with the large science aperture (lsa) and the g160m grating. We'll also have it compute the number of counts in one pixel at 1504 å. The spectral data for Feige 110 are read from the table feige110_stis_001.fits in the directory crcalspec$. The calculated spectrum, in units of counts per pixel, is written to the table hrsobs.fits. We use epar countrate to set the task parameters as follows:
Figure 5.10: Example Countrate Parameter Settings
spectrum = "crcalspec$feige110_stis_001.fits" Spectrum to calculate magnitude = " " Magnitude and passband of spectrum instrument = "hrs" Science instrument (detector = " ") Detector used (spec_elem = "g160m") Spectral elements used (aperture = "lsa") Aperture / field of view (cenwave = 1495.) Central wavelength (HRS and STIS only) (exptime = 1800.) Exposure time in seconds (reddening = 0.) Interstellar reddening E(B-V) (redlaw = "gal1") Reddening law used (gal1|gal2|gal3|smc|lmc|xgal (output = "hrsobs.fits") Output table name (form = "counts") Form for output data (magform = "vegamag") Form for magnitude (wavecat = "synphot$data/wavecat.dat") Catalog of wavelength tables (refwave = 1504.) Reference wavelength (verbose = yes) Print results to STDOUT ? (flux_tot = INDEF) Estimated total flux (output) (flux_ref = INDEF) Estimated flux at reference wavelength (output) (refdata = "") Reference data


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The output on your screen will be the following:
Mode = band(hrs,g160m,lsa) Spectrum: crcalspec$feige110_stis_001*1800. Pivot Equiv Gaussian Total Flux Flux at 1504 A Wavelength FWHM COUNTS COUNTS 1579.611 636.7933 1902314. 3226.052

These results indicate an integrated flux of about 1.9 million counts over the whole spectrum, with approximately 3226 total counts in the pixel at 1504 å. Figure 5.11 shows the resulting spectrum as plotted using the STSDAS task plspec (e.g., plspec none hrsobs counts wave=hrsobs top=5000 bottom=2500).
Figure 5.11: Plot of Countrate Example Spectrum

5000

SYNPHOT.PLSPEC

REFSPEC = hrsobs.tab AREA (cm^2) = 45238.93 4500

DETECTED COUNTS (Area-1 s-1)

4000

3500

3000

2500

1480

1485

1490

1495

1500

1505

1510

WAVELENGTH (A)

For a second example, let's calculate the total number of counts expected in a 600 second integration of a star with a spectrum similar to that of HZ 2 having a V magnitude of 17.5, using the WFPC2 PC chip (chip 1) and F785LP filter. We'll also redden the spectrum by E(B-V)=0.05. Here


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are the parameter settings and the resulting total counts, in units of DNs, recorded in the flux_tot parameter:
Figure 5.12: Second Countrate Example Parameter Settings spectrum magnitude instrument (detector (spec_elem (aperture (cenwave (exptime (reddening (redlaw (output (form (magform (wavecat (refwave (verbose (flux_tot (flux_ref (refdata = = = = = = = = = = = = = = = = = = = "crcalspec$hz2_005.fits" Spectrum to calculate "17.5 V" Magnitude and passband of spectrum "wfpc2" Science instrument "1,a2d7" ) Detector used "f785lp" ) Spectral elements used "") Aperture / field of view INDEF) Central wavelength (HRS and STIS only) 600.) Exposure time in seconds 0.05) Interstellar reddening E(B-V) "gal1") Reddening law used (gal1|gal2|gal3|smc|lmc|xgal) "none") Output table name "COUNTS") Form for output data vegamag) Form for magnitude synphot$data/wavecat.dat) Catalog of wavelength tables INDEF) Reference wavelength yes) Print results to STDOUT ? INDEF) Estimated total flux (output) INDEF) Estimated flux at reference wavelength (output) ) Reference data

The output to the screen will be:
Mode = band(wfpc2,1,a2d7,f785lp) Spectrum: rn(crcalspec$hz2_005.fits*ebmvx(0.05,gal1), band(v), 17.5,vegamag)*600. Pivot Equiv Gaussian Total Flux Wavelength FWHM COUNTS 8458.758 937.9294 8353.222

5.6

Fitband
The fitband task fits a model passband to a known passband function stored in a throughput table. The user specifies a model expression containing up to nine free variables and initial values for the variables. The task then searches for values that minimize the residuals between the model and known passband. When the task finds the optimal solution, it writes the final values of the variables back to the parameter file. Fitting is done by one of two available methods: the Levenberg-Marquardt method or the downhill simplex method, sometimes referred to as the "amoeba" method. The downhill simplex method is slower than the Levenberg-Marquardt method because it requires more iterations to converge to a solution. In compensation, however, it converges


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to the solution over a larger range of initial values than the Levenberg-Marquardt method. In either case, the initial values for the free variables should be as accurate as possible, as neither method will converge to a solution from arbitrarily chosen initial values. If the initial values are outside the range of convergence, the task may either compute a false solution, or wander outside the range where the model expression is defined and terminate with an error. The Levenberg-Marquardt code is from the minpack library at Argonne National Laboratory. The downhill simplex method was adapted from Numerical Recipes by Press et al. (1992). The task has a relatively long list of parameters (Figure 5.13).
Figure 5.13: Fitband Parameters input = obsmode (output (ftol (maxiter (nprint (slow (equal (vone (vtwo (vthree (vfour (vfive (vsix (vseven (veight (vnine (refdata Observed bandpass Model bandpass Table containing fitted bandpass Fractional tolerance termination condition Maximum number of iterations Number of iterations between diagnostic prints Use slow method (simplex) to compute fit? Use equal weighting on the data points? Value of variable one Value of variable two Value of variable three Value of variable four Value of variable five Value of variable six Value of variable seven Value of variable eight Value of variable nine Reference data

= = = = = = = = = = = = = = = = =

none) 1e-05) 500) 0) no) no) INDEF) INDEF) INDEF) INDEF) INDEF) INDEF) INDEF) INDEF) INDEF) )

The input parameter specifies the name of a table containing a known throughput function. This table must contain, at minimum, columns of wavelength and throughput values, and may contain an optional error column. If the table is in FITS or STSDAS format, the column names must be WAVELENGTH, THROUGHPUT, and ERROR. If it is a text file, the wavelength, throughput, and error values must be in the first, second, and third columns, respectively. If present, the ERROR column data are used for weighting the data points during the fit (see below). The obsmode parameter specifies the model passband expression to be fitted to the input throughput table data. The obsmode may contain any valid synphot passband functions, with up to nine variables substituted for the arguments of those functions. The variables in the expression are indicated by a dollar sign followed by a digit from 1 to 9 (e.g., "$3"). The initial values of the variables are given in the task parameters vone


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through vnine (see below). All variables not used should be set to INDEF. Variables in the expression should be consecutive; for example if the model contains three variables, they should be $1, $2, and $3, not $1, $3, $7. The obsmode expression may be placed in a file, if desired, in which case the name of the file is specified as obsmode=@filename. (See "Filename specifications" on page 19 for important side effects of using the @filename syntax.) Placing the obsmode expression in a file is necessary if the expression is too long to fit in the task parameter (63 characters max). If the expression is placed in a file, it may be split over more than one line wherever a blank is a legal character in the expression. The output parameter specifies the name of the output table that will contain the final fitted passband function. If output is set to "none" or left blank, then no output table will be produced. The output table contains the model passband (obsmode) expression evaluated with the fitted values of the free variables. The header of the table also contains the names of the graph and component lookup tables and the model expression. The ftol parameter sets the fractional tolerance convergence criterion. Iteration of the least squares fit ceases when the scaled distance between two successive estimates of the free variables is less than this value. Each component of the scaled distance is scaled by dividing the difference between the two estimates by half their sum. Note that the fit solution may not converge to an arbitrarily small value; instead it may cycle between several values. Setting ftol to too small a value may therefore result in failure to converge. The maxiter parameter sets the maximum number of iterations to be performed. If convergence is not achieved in this number of iterations, then the task stops with a warning message to that effect. The nprint parameter specifies the number of iterations to perform between successive printings of diagnostic information to STDERR (usually your terminal). If nprint=0, there will be no diagnostic information printed. The diagnostic prints contain the iteration number, the chi-squared value, and the model passband with the current values of the variables. The slow parameter selects which fitting method to use. If slow=no (the default), the Levenberg-Marquardt method is used. If slow=yes, the downhill simplex method is used. The equal parameter indicates whether or not to weight the data points when computing the fit. If equal=no and the input table contains a column of error values, then the data points will be weighted by the errors. Points with indefinite, negative, or zero-valued errors are not used in the fit. If equal=yes or no valid error values are specified in the input table, then the data points will receive equal weights.


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The vone through vnine parameters are used to specify the initial values of the variables used in the model passband (obsmode) expression. Initial (non-INDEF) values must be set for variables in use before running the task. At the conclusion of the fitting process, these parameters will be updated with the final variable values. Any variables that are not used in the model should be set to INDEF. See Section 3.4, "Variable Substitution (VZERO)," on page 26 for a discussion of variable substitution.

5.6.1 Example
This example demonstrates how to determine values for the central wavelength, FWHM, and scale factor of a gaussian passband that best fits the shape of the F555W filter from the WFPC2. The equal parameter is set to "yes" because the error values in the throughput table for the F555W filter are all zero. We start with initial guesses of 5500 and 500 å for the central wavelength and FWHM, respectively, and 1.0 for the scale factor. Diagnostic information is printed after each iteration and the final fitted passband data is saved in the table fit555w.fits.
sy> fitband crwfpc2comp$wfpc2_f555w_006_syn.fits "gauss($1,$2)*$3" \ >>> out=fit555w.fits nprint=1 vone=5500 vtwo=500 vthree=1 equal+

While the task is running, the following information will appear:
irep = 1 chisq = 0.069752 exp = gauss(5500.,500.)*1.01 irep = 2 chisq = 0.038892 exp gauss(5447.017,1048.002)*0.6551079 irep = 3 chisq = 0.012754 exp gauss(5204.142,1900.48)*0.8528795 irep = 4 chisq = 0.008139 exp gauss(5317.027,1230.885)*1.017857 irep = 5 chisq = 0.005766 exp gauss(5250.305,1477.974)*0.9963291 irep = 6 chisq = 0.005529 exp gauss(5265.997,1366.231)*1.050334 irep = 7 chisq = 0.005493 exp gauss(5256.394,1402.266)*1.039902 irep = 8 chisq = 0.005492 exp gauss(5259.135,1388.974)*1.045587 irep = 9 chisq = 0.005491 exp gauss(5258.057,1393.395)*1.043876 irep = 14 chisq = 0.005491 exp gauss(5258.118,1393.203)*1.04391 irep = 15 chisq = 0.005478 exp gauss(5258.145,1393.12)*1.033594 Final solution: gauss(5258.118,1393.203)*1.033575 = = = = = = = = = =


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You can plot the fitted gaussian and overplot the F555W passband for comparison using the plband task:
sy> plband fit555w.fits left=2500 right=8000 sy> plband crwfpc2comp$wfpc2_f555w_006_syn.fits ltype=dashed top=1.25 append+

The resulting plot is shown in Figure 5.14.
Figure 5.14: Results from Example Fitband Run
1.25 SYNPHOT.PLBAND

OBSMODE = fit555w OBSMODE = crwfpc2comp$wfpc2_f555w_001 1

.75

PASSBAND

.5

.25

0 3000 4000 5000 6000 7000 8000

WAVELENGTH (A)

5.7

Fitspec
The fitspec task allows you to fit a spectrum model to spectral data stored in a table. You specify a model spectrum using any valid synphot spectrum expression, including up to nine free variables and their initial values. The task then searches for values for those variables that minimize the residuals between the model spectrum and the known spectrum stored in the table. When the task finds the optimal solution, it writes the fitted values of the variables back to the parameter file and prints the expression with the final variable values. Using the final parameter values you could restart the task to perform more iterations. Fitting is done by one of two available methods: the Levenberg-Marquardt method or the downhill simplex method, sometimes


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referred to as the "amoeba" method. The downhill simplex method is slower than the Levenberg-Marquardt method because it requires more iterations to converge to a solution. In compensation, however, it converges to the solution over a larger range of initial values than the Levenberg-Marquardt method. In either case, the initial values for the free variables should be as accurate as possible, as neither method will converge to a solution from arbitrarily chosen initial values. If the initial values are outside the range of convergence, the task may either compute a false solution, or wander outside the range where the model expression is defined and terminate with an error. The Levenberg-Marquardt code is from the minpack library at Argonne National Laboratory. The downhill simplex method was adapted from Numerical Recipes by Press et al. (1992). The fitspec task parameter list (Figure 5.15) is nearly identical to that of the fitband task.
Figure 5.15: Fitspec Parameters input = spectrum (output (ftol (maxiter (nprint (slow (equal (vone (vtwo (vthree (vfour (vfive (vsix (vseven (veight (vnine (refdata Observed spectrum Model spectrum Table containing fitted spectrum Fractional tolerance termination condition Maximum number of iterations Number of iterations between diagnostic prints Use slow method (simplex) to compute fit? Use equal weighting on the data points? Value of variable one Value of variable two Value of variable three Value of variable four Value of variable five Value of variable six Value of variable seven Value of variable eight Value of variable nine Reference dat

= = none) = 1e-05) = 500) = 0) = no) = no) = INDEF) = INDEF) = INDEF) = INDEF) = INDEF) = INDEF) = INDEF) = INDEF) = INDEF) =)

The input parameter specifies the name of a table containing a known spectrum. This table must contain, at minimum, columns of wavelength and flux values, and may contain optional error and spectral resolution column. If the table is in FITS or STSDAS format, the column names must be WAVELENGTH, FLUX, STATERROR, and FWHM. If it is a text file, the wavelength, flux, error, and FWHM values must be in the first, second, third, and fourth columns, respectively. If present, the contents of the STATERROR column are used for weighting the data points during the fit (see below). The FWHM column data are not used by this task.


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65

The spectrum parameter specifies the model spectrum expression to be fitted to the input spectrum table data. The spectrum may contain any valid synphot spectrum functions, with up to nine variables substituted for the arguments of those functions. The variables in the expression are indicated by a dollar sign followed by a digit from 1 to 9 (e.g. "$3"). The initial values of the variables are given in the task parameters vone through vnine (see below). All variables not used should be set to INDEF. The model expression should not skip variables; for example if the model contains three variables, they should be $1, $2, and $3, not $1, $3, and $7. The spectrum expression may be placed in a file, if desired, in which case the name of the file is specified as spectrum=@filename. (See "Filename specifications" on page 19 for important details about the @filename syntax.) Placing the spectrum expression in a file is necessary if the expression is too long to fit in the task parameter (63 characters max). If the expression is placed in a file, it may be split over more than one line wherever a blank is a legal character in the expression. The output parameter specifies the name of the output table that will contain the final fitted spectrum. If output is set to "none" or left blank, then no output table will be produced. The output table contains the model spectrum expression evaluated with the fitted values of the free variables. The flux units for the data in the output table are the same as that of the input spectrum. The header of the output table also contains the names of the graph and component lookup tables and the model expression. The ftol parameter sets the fractional tolerance convergence criterion. Iteration of the least squares fit ceases when the scaled distance between two successive estimates of the free variables is less than this value. Each component of the scaled distance is scaled by dividing the difference between the two estimates by half their sum. Note that the fit solution may not converge to an arbitrarily small value; instead it may cycle between several values. Setting ftol to too small a value may therefore result in failure to converge. The maxiter parameter sets the maximum number of iterations to be performed. If convergence is not achieved in this number of iterations, then the task stops with a warning message to that effect. The nprint parameter specifies the number of iterations to perform between successive printings of diagnostic information to STDERR (usually your terminal). If nprint=0, there will be no diagnostic information printed. The diagnostic prints contain the iteration number, the chi-squared value, and the model spectrum with the current values of the variables. The slow parameter selects which fitting method to use. If slow=no (the default), the Levenberg-Marquardt method is used. If slow=yes, the downhill simplex method is used.


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The equal parameter indicates whether or not to weight the data points when computing the fit. If equal=no and the input table contains a column of error values, then the data points will be weighted by the errors. Points with indefinite, negative, or zero-valued errors are not used in the fit. If equal=yes or no valid error values are specified in the input table, then the data points will receive equal weights. The vone through vnine parameters are used to specify the initial values of the variables used in the model spectrum (spectrum) expression. Initial (non-INDEF) values must be set for variables in use before running the task. At the conclusion of the fitting process, these parameters will be updated with the final variable values. Any variables that are not used in the model should be set to INDEF. See Section 3.4, "Variable Substitution (VZERO)," on page 26 for a discussion of variable substitution syntax.

5.7.1 Example
Let's say you have an observed spectrum of an A-type star that's reddened by some unknown amount. We'll use fitspec to compute the amount of extinction in the observed spectrum by comparing it to an unreddened spectrum of the prototypical A0 V star Vega that is in the HST standards crcalspec$ directory. For the purposes of this demonstration we'll create a spectrum of our hypothetical reddened star using calcspec as follows:
sy> calcspec "crgridjac$jc_19.fits*ebmv(0.073)" \ Astar_ebv073.fits form=flam

This uses the observed spectrum of an A-type star from the Jacoby-Hunter-Christian spectral library (see section A.8) and applies reddening equivalent to E(B­V)=0.073. The reddened spectrum is written to the table Astar_ebv073 in units of flam. Now we run fitspec using the Astar_ebv073.fits table as our observed spectrum (input) and ask fitspec to compute a model based on the unreddened Vega spectrum, solving for the amount of extinction that best fits the observed spectrum. Since our observed star is much fainter than Vega, we'll also need to solve for a renormalization value. Using calcphot we determine that the observed star has a V magnitude of about 9; we'll use that as the initial value for the renormalization variable. We use epar to set the fitspec parameters as follows:


Fitspec Figure 5.16: Example Fitspec Parameter Settings
input spectrum (output (ftol (maxiter (nprint (slow (equal (vone (vtwo (vthree ... (vnine (refdata = = = = = = = = = = =

67

Astar_ebv073.fits Observed spectrum rn(crcalspec$alpha_lyr_stis_002.fits,band(v),$1,vegamag)*ebmv($2) Model spectrum Astar_fit.fits) Table containing fitted spectrum 1e-05) Fractional tolerance termination condition 500) Maximum number of iterations 1) Number of iterations between diagnostic prints no) Use slow method (simplex) to compute fit? yes) Use equal weighting on the data points? 8.99492783993) Value of variable one 0.0850384839994)Value of variable two INDEF) Value of variable three Value of variable nine Reference data

= INDEF) =)

Final solution: rn(crcalspec$alpha_lyr_stis_002.fits,band(v),8.994928, vegamag)*ebmv(0.08503857):
1 2 3 4 5 chisq=0.003964 chisq=2.307E-4 chisq=1.797E-4 chisq=1.799E-4 chisq=1.796E-4 exp=rn(alpha...,9.,vegamag)*ebmv(0.01) exp=rn(alpha...,9.0587,...)*ebmv(0.0624) exp=rn(alpha...,9.0333,...)*ebmv(0.0795) exp=rn(alpha...,9.0336,...)*ebmv(0.0799) exp=rn(alpha...,9.0336,...)*ebmv(0.0791)

Final solution: rn(alpha_lyr_001,band(v),9.0336,vegamag)*ebmv(0.07914)

We can plot the results, comparing the observed spectrum with the fitted spectrum, using plspec:
sy> plspec "" Astar_ebv073.fits flam sy> plspec "" Astar_fit.fits flam append+ ltype=dotted

This plot is shown in Figure 5.17.


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Chapter 5: Task Descriptions Figure 5.17: Results from Fitspec
SYNPHOT.PLSPEC 1.75E-12 REFSPEC = Astar_ebv073 REFSPEC = Astar_fit 1.50E-12

FLAM (ergs cm-2 s-1 A-1)

1.25E-12

1.00E-12

7.50E-13

5.00E-13

2.50E-13 4000 5000 6000 7000 WAVELENGTH (A)

5.8

Fitgrid
The fitgrid task is useful for finding the best match to a given input spectrum from a list (or grid) of other spectra. The task scales every spectrum in the list to the same flux as the input spectrum, and keeps track of the best fits. The task determines a final fit by interpolating between the two best fits in the input list. This is useful for getting a quick scale factor to fit a spectrum to data, for example, for use as a starting point of a more refined spectrum fit to be done with the fitspec task. The resulting fit can optionally be saved to an output spectrum table. The fitgrid task uses the same fitting methods as the fitband and fitspec tasks, namely the Levenberg-Marquardt and downhill simplex ("amoeba") methods. For more details about these methods please see the description of the fitband or fitspec task. The parameter list for fitgrid (Figure 5.18) is similar to those of the fitband and fitspec tasks.


Fitgrid Figure 5.18: Fitgrid Parameters input spectrum (output (vzero (ftol (maxiter (nprint (slow (equal (refdata = = = = = = = = = = Observed spectrum List of spectra Table containing the fitted spectrum List of values for variable zero Fractional tolerance termination condition Maximum number of iterations Number of iterations between diagnostic prints Use slow method (simplex) to compute fit? Use equal weighting on the data points? Reference data

69

"none") " ") 1.0E-5) 500) 0) no) no) "")

The input parameter specifies the name of a table containing a known spectrum. This table must contain, at minimum, columns of wavelength and flux values, and may contain optional error and spectral resolution column. If the table is in FITS or STSDAS format, the column names must be WAVELENGTH, FLUX, STATERROR, and FWHM. If it is a text file, the wavelength, flux, error, and FWHM values must be in the first, second, third, and fourth columns, respectively. If present, the contents of the STATERROR column are used for weighting the data points during the fit (see below). The FWHM column data are not used by this task. The spectrum parameter specifies the list of spectra to be compared to the input spectrum data. The spectrum string may contain any valid synphot spectrum expressions, with the option of using the variable vzero ($0) as an argument within the string. During execution, the values of vzero will be substituted for $0, automatically creating a list of spectra. Alternatively, several individual spectrum expressions may be stored in a file, one per line, in which case the name of the file is specified as spectrum=@filename. (See "Filename specifications" on page 19 for important details about the @filename syntax). The output parameter specifies the name of the output table that will contain the final fitted spectrum. If output is set to "none" or left blank, then no output table will be produced. The output table contains the best fit from the list of spectra. The flux units for the output data are the same as that of the input spectrum. The header of the output table also contains the names of the graph and component lookup tables and the model expression. The vzero parameter contains a list of values that are substituted for variable zero ($0) wherever it appears in the spectrum expression. See Section 3.4, "Variable Substitution (VZERO)," on page 26 for a discussion of variable substitution. The ftol parameter sets the fractional tolerance convergence criterion. Iteration of the least squares fit ceases when the scaled distance between two successive estimates of the free variables is less than this value. Each


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component of the scaled distance is scaled by dividing the difference between the two estimates by half their sum. Note that the fit solution may not converge to an arbitrarily small value; instead it may cycle between several values. Setting ftol to too small a value may therefore result in failure to converge. The maxiter parameter sets the maximum number of iterations to be performed. If convergence is not achieved in this number of iterations, then the task stops with a warning message to that effect. The nprint parameter specifies the number of iterations to perform between successive printings of diagnostic information to STDERR (usually your terminal). If nprint=0, there will be no diagnostic information printed. The diagnostic prints contain the iteration number, the chi-squared value, and the model spectrum with the current values of the variables. The slow parameter selects which fitting method to use. If slow=no (the default), the Levenberg-Marquardt method is used. If slow=yes, the downhill simplex method is used. The equal parameter indicates whether or not to weight the data points when computing the fit. If equal=no and the input table contains a column of error values, then the data points will be weighted by the errors. Points with indefinite, negative, or zero-valued errors are not used in the fit. If equal=yes or no valid error values are specified in the input table, then the data points will receive equal weights.

5.8.1 Examples
Let's fit a series of spectra from the Bruzual-Persson-Gunn-Stryker spectral library (see section A.7) to the spectrum of P177D, which is again taken from the HST standards directory crcalspec. The list of library spectra are specified in the file grid.lis as follows:
crgridbpgs$bpgs_33.fits crgridbpgs$bpgs_35.fits crgridbpgs$bpgs_36.fits crgridbpgs$bpgs_45.fits

The fit results are saved in the table p177d_fit.fits. fitgrid is run as follows:
sy> fitgrid crcalspec$p177d_stis_001.fits out=p177d_fit.fits @grid.lis

The final solution is:
0.7155979 * 4.151929E-6 * (crgridbpgs$bpgs_45.fits) + (1. - 0.7155979) * 4.382411E-6 * (crgridbpgs$bpgs_36.fits)


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For a second example we'll make use of variable zero (vzero) to automatically generate a list of blackbody spectra of varying temperatures to be fit to the spectrum of the same star:
sy> fitgrid crcalspec$p177d_stis_001.fits out=bb_fit.fits vzero=10e3-30e3x1e3 equal=yes "bb($0)" \

The vzero string gives us a list of blackbody spectra having temperatures from 10000 to 30000 K, in steps of 1000 K. The resulting spectrum is stored in the table bb_fit.fits. The final solution is:
5.574925 * 0.683679 * (bb(10000.)) + (1. - 5.574925) * 0.5202777 * (bb(11000.))

We can then compare the models with the P177D spectrum using plspec as follows (see Figure 5.19):
sy> plspec "" bb_fit.fits flam ltype=dotted sy> plspec "" crcalspec$p177d_stis_001.fits flam append+ sy> plspec "" p177d_fit.fits flam append+ ltype=dashed Figure 5.19: Fitgrid Results


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5.9

Genwave
The genwave task creates a wavelength set based on user-specified values for the minimum and maximum wavelengths and the sampling interval. The sampling interval may be expressed in terms of Angstroms per pixel or in terms of kilometers per second per pixel. The resulting wavelength set is stored in a FITS or STSDAS table. The task parameters are listed in Figure 5.20.
Figure 5.20: Genwave Parameters output minwave maxwave dwave (dvelocity (wavecol = = = = INDEF = INDEF) = WAVELENGTH) Wavelength set table name Minimum of wavelength range (Angstroms) Maximum of wavelength range (Angstroms) Wavelength interval (Angstroms/pixel) Velocity interval (km/s/pixel) Wavelength set table column name

The output wave set is a single column table with the column label specified by parameter wavecol. The default setting of wavecol = WAVELENGTH is the column name expected by other synphot tasks that use a user-specified wavelength set. The wavelength values written to the table are in units of Angstroms. The wavelength interval between sample points, in Angstroms per pixel, is normally set by the value of the dwave parameter. If dwave=INDEF, then the value of the dvelocity parameter is used instead. In this case, the sample interval is expressed by the user in units of km per second per pixel, and the equivalent sampling in Angstroms per pixel is computed by the task. Note that the output wave set is always expressed in units of Angstroms, regardless of which sampling specification method was used. There is a set of ASCII wavelength tables in the STSDAS synphot$data directory which can be used with any of the synphot tasks, so it is not always necessary to create custom wave sets. This directory contains tables for each grating and echelle order for the HRS and FOS instruments. The wavelength grids in these tables cover the range and are sampled at the (sometimes non-linear) resolution appropriate for each grating as used in a standard observing mode for each instrument.

5.9.1 Examples
The first example shows how to generate a wavelength set having a range of 3000 to 8000 å, with a sampling interval of 2 å per pixel. The wavelength set will be written to the table wave2.fits in a column labeled WAVELENGTH.
sy> genwave wave2.fits 3000 8000 2


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Next, we'll generate a wavelength set having the same range as the one above, but have the sampling interval be equivalent to 100 km/s/pixel.
sy> genwave wave_kms.fits 3000 8000 INDEF dv=100

5.10

Grafcheck
The grafcheck task reads an instrument graph table and checks it for four types of errors: · Undefined component name, keyword, input node number, or output node number. · Output node number less than input node number. · Identical keywords in two or more nodes with the same input node. (Leading blanks and case are ignored in determining uniqueness of keyword names; names that differ only in case are considered identical.) · A row cannot be reached from the graph's starting node. When errors are detected, a row will be printed for each type of error detected, along with the offending row. When a row is in error, the component name is displayed, followed by the keyword, the input node, and the output node numbers. Component names and keywords are converted to lower case in the output and are enclosed in quotation marks. No output is produced if no errors are detected. All output from the task is directed to STDOUT. The only task parameter is grftable, which has the value "mtab$*_tmg.fits" by default, and is used to specify the name of the graph table to be checked.

5.10.1 Example
Check the graph table hstgraph.fits for errors:
sy> grafcheck hstgraph.fits


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5.11

Graflist
The graflist task prints the names of all components in an instrument graph table downstream from a specified starting component. The specified starting component is referred to as the root. A component is considered to be downstream from the root if a path passes through both the root and the component and the root appears first in the path. A root is always considered to be downstream from itself, so at least one component name will always be printed when the task is executed. The list of component names is printed in the order that they occur along the path. When component names are printed, each component name is indented to show the distance between it and the root. There are two task parameters:
grftable="mtab$*_tmg.fits" compname="mtab$*_tmc.fits" node Instrument graph table Component name of starting

The grftable parameter specifies the name of the instrument graph table to be searched. The compname parameter specifies the name of the root component. The component name is not case sensitive and leading and trailing blanks will not affect the match. If more than one component in the graph table matches compname, the component with the smallest value in the INNODE column will be used. The component name can be made unique by optionally specifying an INNODE number as part of compname. To do this, the INNODE number must follow the component name, separated by a white space. If no value is passed to compname, the entire graph will be listed.

5.11.1 Examples
List all components that are downstream from "hrs_echa":
sy> graflist mtab$*_tmg.fits hrs_echa

List all components that are downstream from the component "clear" that has an INNODE value of 1000:
sy> graflist mtab$*_tmg.fits "clear 1000"


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5.12

Grafpath
This task returns the ordered list of throughput filenames that comprise the model used by synphot when performing spectral calculations for a given observation mode. The other tasks compute the throughput for an observation mode by multiplying these individual files together. This task is useful for understanding the results returned by other tasks, and also for confirming that a graph table is returning the expected results for a specified obsmode. The only task parameter (aside from the refdata PSET) is obsmode, which is specified in the usual way. All output from the task is directed to STDOUT.

5.12.1 Examples:
To examine the list of files used to model WFPC2 with the f122m filter, issue the command:
sy> grafpath wfpc2,f122m

This produces the following output:
crotacomp$hst_ota_007_syn.fits crwfpc2comp$wfpc2_optics_006_syn.fits crwfpc2comp$wfpc2_f122m_006_syn.fits crwfpc2comp$wfpc2_dqewfc4_005_syn.fits

Here you can see the throughput files used for the HST OTA, the WFPC2 optics, the f122m filter, and the DQE of the detector. These filenames can then be examined using tread or by some other means. The results for HST observation modes produce a list of files. Non-HST modes, such as those that simply specify a photometric bandpass, produce just one file that contains the bandpass definition as it is implemented in synphot. You can use grafpath to determine which file is used if the unadorned bandpass "r" is given:
sy> grafpath r

which produces as output
crnonhstcomp$cousins_r_003_syn.fits


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5.13

Imspec
The imspec task can be used to convert one-dimensional images into STSDAS or FITS tables and to convert synphot-style tables into images. The type of conversion to perform (image to table, or table to image) is determined automatically from the type of the input file. More than one file may be converted at a time by using a list of input and output files. Wavelength information may also be copied along with flux values (see below). The task parameters are listed in Figure 5.21.
Figure 5.21: Imspec Parameters

input output (wave (inform (outform (olength (badpix (refdata

= = = = = = = =

" ") "counts") "counts") INDEF) 0.) "")

List of input files List of output files Optional wavelength images Form of input spectrum Form of output spectrum Length of output file Value to substitute for INDEF in output image Reference data

The input and output file types may be either images or tables. The task will determine the type of the specified input file and create an output file of the opposite type. If a wavelength file name is specified, the number of wavelength files must match the number of input and output files. If both input and output files are FITS files, no header information is preserved. imspec constructs minimal headers for the output files.

5.13.1 If the input file is an image:
If the input file is an image, then the output file will be a FITS or STSDAS table containing columns of WAVELENGTH and FLUX. The wavelength values will be in units of Angstroms. The units of the flux values may be selected using the outform parameter (see below). If no wavelength file is specified, the World Coordinate System (WCS) information in the input image header will be used to generate a wavelength set to be written to the output table. If a wavelength image is supplied along with an input image, the WCS in the input image header is ignored and the wavelengths are copied from the supplied wavelength image, which are assumed to be in a one-to-one correspondence with the flux values in the input image.


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If the input file is a multigroup (GEIS) image, only one data group can be copied at a time. If the group number is not specified in the input file name, the first group will be copied. If the input file is a multi-extension FITS image, you must specify which HDU is to be copied in the filename, e.g. manyimages.fits[2] to copy the second extension. If the output file is a FITS table, the table data will be placed in the first extension of the output FITS file. A primary HDU will be created with a minimal header.

5.13.2 If the input file is a table:
If the input file is a table, the output file will be a one-dimensional image. The number of output files must match the number of input files. The input table must contain two columns labeled WAVELENGTH and FLUX (or FLUX1). All other columns in an input table will be ignored. The values in the wavelength column must be in monotonic order. If wavelength and flux units are specified in the table header, they must be units supported by the synphot package. If the input file is a table and a wavelength image is specified, the flux column in the input table is copied to the output image, and the wavelength column in the input table is copied to the specified wavelength image. If the output file is an image and no wavelength image is specified, WCS information will be computed from the input wavelength array and written to WCS header keywords in the output image. If the input file is a multi-extension FITS table, and no extension is specified in the filename, its first extension will be copied into an image. Other extensions may be specified as part of the input filename, e.g. manytables.fits[2] will select the second extension. If the output file is a FITS image, the image data will be placed in the primary HDU of the FITS file.

5.13.3 Other parameters:
The inform parameter is used to specify the flux units when the input file is an image. If the input file is a table, the flux units are read from the flux column units in the table header and this parameter is ignored (unless the column units are blank). The outform parameter is used to specify the desired output flux units. Units conversion, if necessary, is performed by the task. The olength parameter may be used to specify the desired length of the output file. If set to INDEF (the default), the length of the output file


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will be the same as the length of the input file. If the output file is an image, olength specifies the number of image pixels. If the output is a table, olength specified the number of table rows. The value of the badpix parameter is used to replace INDEF flux values from an input table when they are copied to an output image. As with all other synphot tasks, the parameter refdata specifies the name of the parameter set (pset) containing certain necessary reference data. The only parameter from this pset used by the imspec task is area, the telescope collecting area.

5.13.4 Examples
Copy the synphot-format table for the standard star GD71, contained in table gd71_stis_001.fits in the crcalspec$ directory, to the image gd71_image.fits. Since no wavelength image name is specified, the wavelength data in the input table will be used to compute WCS header keyword values for the output image.
sy> imspec crcalspec$gd71_stis_001.fits gd71_image.fits outform=flam

Copy an FOS spectral image into a table with the same rootname as the input image, but an extension of .fits. Use the corresponding FOS wavelength image (image with a .c0h extension) to specify the wavelength array to be written to the output table. Because the input file is an image, we must tell the task what the input flux units (inform) are.
sy> imspec y15v0403t.c1h y15v0403t.fits wave=y15v0403t.c0h \ >>> inform=flam outform=flam

(Although only the header files (.c0h,.c1h) are explicitly mentioned in the command, the corresponding data files (.c0d, .c1d) must also be present in the directory.)

5.14

Mkthru
The mkthru task converts an ASCII file, FITS table, or STSDAS binary table into a throughput table for installation in CDBS. The table will have the required header keywords, column names, column units, and column formats. If the necessary header keywords are not present in the input file, the task will query the user for the appropriate values. Because the task parameters that read this information use query mode, you will be queried for this information even if you set them in the parameter editor. (The values you set will be displayed as default values.)


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Column names can be specified in ASCII files by placing them on the first line and setting the hidden parameter title to yes. The task uses default values for the column information if it is not present in the input file. The default column names are WAVELENGTH, THROUGHPUT, and ERROR. The default column units are ANGSTROMS, TRANSMISSION, and TRANSMISSION. The default print formats are%10.1f,%12.5g, and%12.5g. (If necessary, these values can be later modified by using the tchcol task on the output file.) The task parameters are listed in Figure 5.22.
Figure 5.22: Mkthru Parameters input instrume compname useafter pedigree descrip comment (title (verbose = = = = = = = = = filename template instrument name Component name Useafter date Reference file pedigree Description of file Comment about file no) First line of file has column names no) Verbose message switch

The input parameter is a list of input file names. File names may include wild cards. Output files have the same names as the input files, but their extension is changed to fits. Except for title and verbose, all the remaining parameters for this task function as default values for the header keyword of the output file, as described above. The task will look for the matching header keyword in the input file first; only if it is not found will it use the value in the task parameter. The instrument parameter specifies the name of the telescope instrument used in the observation. The compname parameter specifies the name of the component associated with the throughput file. The useafter parameter specifies the start of the date range for which the throughput file is valid. The date should be in the form "mmm dd yyyy" where "mmm" is a three letter month abbreviation.

Important: The useafter parameter functions differently for synphot files than for other CDBS reference files. The CDBS tool used to construct the component lookup table always selects the throughput file with the latest useafter date. Therefore, this parameter should always be set to the current date to ensure that the new throughput file will be picked up.


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The pedigree parameter records the source of the information in the throughput file. It should have one of the following values: INFLIGHT, GROUND, MODEL, or DUMMY. The descrip parameter contains a short description of the throughput file. The comment parameter contains a comment on the throughput file. If the title parameter is set to yes, the column names are taken from the first line of the input file. Otherwise, no column names are produced for the output file. If the verbose parameter is set to yes, the task will display a message after each file is converted to FITS

5.14.1 Examples
Convert a set of ASCII files to FITS format, and let the task prompt for all necessary header keywords.
sy> mkthru *.dat

Convert an STSDAS binary table (which already contains the correct header keywords) to FITS format
sy> mkthru hst_dark.fits

5.15

Modeinfo
This task displays a list of the observation mode keywords available for a particular instrument or filter system, along with information about the use and application of the keywords. For example, modeinfo stis displays information about all the available observation mode keywords for the HST STIS instrument and explains their use and significance to the instrument. This task can also be used to display observation mode information for some of the non-HST filter systems that are supported in Synphot, such as the ground-based "UBV" system. If the user does not supply an instrument parameter, or supplies one for which no information is available, the task will list the available instrument and filter system names. The only task parameter is instrument, which is used to specify the name of the HST instrument to be checked.


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5.15.1 EXAMPLES
To display observation mode information for NICMOS: sy> modeinfo nicmos To display observation mode information for the ground-based UBVRI filter system: sy> modeinfo ubv To display a list of instrument/filter system names for which information is available: sy> modeinfo ""

5.16

Obsmode
The obsmode task displays a list of the observation mode keywords contained in the instrument graph table, usually for a single instrument. For example, "obsmode foc" displays the list of valid observation mode keywords for the FOC. The task is very helpful when you are having trouble remembering the names of all the available keywords for a given instrument. The output is structured so that keywords representing a group of alternative elements at a given point within the instrument's optical path are placed on the same line. An observation mode (obsmode) string could contain no more than one of these keywords at a time. Long lists of keywords are wrapped, however, so that they are able to display on the terminal screen. It should be obvious from the keyword names when a long list has been wrapped. Individual keywords from the graph table are used within the obsmode string of other synphot tasks to specify a unique light path through the telescope and instrument. The throughputs of the individual components in the light path are combined to determine a total throughput for a given observing mode. The keywords contained in the path string are dependent on the structure of the graph table. Default keywords are often allowed in the path string, but it is safest to explicitly include all desired components. In particular, in the current HST graph table, Johnson is the default filter system for UBV, and Cousins is the default for RI. The obsmode task has the following two parameters:
path = (refdata = "") Partial observation mode path Reference data

The path parameter is used to specify a (partial) observation mode which selects the starting node for the output information. The keywords displayed by the task will be the descendants of the last node matched by


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any of the keywords in the path string. Usually, the value of parameter is a single keyword specifying the name of an instrument. example, "acs" specifies that all the keywords that are descendants of acs node in the graph table are to be displayed. If this parameter is blank or set to "none", all the keywords in the graph table will displayed. The refdata parameter specifies the name of the parameter containing the necessary reference data for the task. In the case of obsmode task, the only important reference data is the name of instrument graph table (grtbl) to be searched.

this For the left be set the the

5.16.1 Examples
Display the observation mode keywords for the WFPC2:
sy> obsmode wfpc2

Display the list of central wavelengths available for STIS with the e140h grating:
sy> obsmode stis,e140h

Display all the keywords in the graph table:
sy> obsmode ""

5.17

Plband
The plband task is similar to calcband, except that it produces a plot as its output rather than a table, and is used to plot a set of synthetic or instrumental passbands. The user has control over certain plot attributes, such as the displayed plot limits and line styles, and can append new plots to a previous one that was generated by plband. The task parameters are listed in Figure 5.23.


Plband Figure 5.23: Plband Parameters obsmode (left (right (bottom (top (normalize (ylog (append (ltype = (device (wavetab (refdata = = INDEF) = INDEF) = INDEF) = INDEF) = no) = no) = no) solid) = stdgraph) =) =)

83

Instrument mode or @list x value for left side of plot x value for right side of plot y value for bottom of plot y value for top of plot Normalization all curves to 1? Take log of y values? Append to existing plot? Line type: clear,solid,dashed,dotted,dotdash Graphics device Wavelength table name Reference data

The obsmode parameter specifies the passband(s) to be plotted. Individual passbands can be added, subtracted, multiplied or divided by one another using the +, -, *, and / operators, respectively. See Section 3.2.2 for more details concerning all of the supported mode functions. Lists of obsmode strings may be placed in a text file, one per line, and specified as obsmode=@filename. (See "Filename specifications" on page 19 for important side effects of using the @filename syntax). The left, right, bottom, and top parameters specify the minimum and maximum wavelength and throughput limits for the plot. If set to INDEF, the task will set them based on the limits of wavelength set and passband values. The normalize parameter can be used to normalize all passbands to a maximum value of 1. If normalize=no, each band is plotted at its intrinsic level. The ylog parameter can be used to create a plot with the y-axis in logarithmic units. If append=yes, the results will be overplotted on an existing plot. The ltype parameter is used to specify the line type to be used for plotting the passband. The available line types are: solid, dashed, dotted, dotdash, and clear. If a list file is used to specify the bands to be plotted, then one line type is used for all the passbands in the list. Null values for the wavetab and refdata parameters will cause the task to use a default wavelength grid (See "Wavelength Table" on page 25.) and the default reference data for the HST observatory (see Section 3.5). The default wavelength grid covers the wavelength range where the passband throughput is non-zero. Wavelengths are spaced logarithmically over this range. If there is more than one passband specified, the range of the default wave set is computed based on the first passband.


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If the wavelength ranges of the passbands differ significantly, a suitable wavelength table that covers the range of all the passbands should be constructed using the genwave task, and supplied as input via the wavetab parameter.

5.17.1 Examples
Plot the WFPC2 F569W passband and compare it to the standard Johnson V passband (overplotted as a dashed line). Normalize both curves to a maximum of 1 and limit the wavelength range of the plot to 4000­7500 å. Results are shown in Figure 5.24.
sy> plband wfpc2,f569w left=4000 right=7500 top=1.25 norm+ sy> plband v norm+ app+ ltype=dashed Figure 5.24: Results of First Sample Plband Run
1.25 SYNPHOT.PLBAND

OBSMODE = wfpc2,f569w OBSMODE = v 1

.75

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.5

.25

0 4500 5000 5500 6000 6500 7000 7500

WAVELENGTH (A)

For the next example, plot the Johnson UBVRI passbands and overplot the Cousins RI passbands (using a dashed line) for comparison. The Johnson bands are listed in the file johnson_ubvri.lis as:
johnson,u johnson,b johnson,v


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Similarly, the Cousins RI passband names are contained in the file cousins_ri.lis as:
cousins,r cousins,i

Because the individual passbands have very different wavelength limits, it's necessary to generate a wave set (using genwave) that runs from 3000 to 12000 å. This wave set is in table johnson_wv.fits. Results are shown in Figure 5.25.
sy> plband @johnson_ubvri.lis wav=johnson_wv.fits top=1.25 sy> plband @cousins_ri.lis wav=johnson_wv.fits app+ lt=dashed Figure 5.25: Results of Second Sample Plband Run
1.25 SYNPHOT.PLBAND

OBSMODE = @johnson_ubvri.lis OBSMODE = @cousins_ri.lis 1

PASSBAND

.75

.5

.25

0

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6000

8000

10000

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WAVELENGTH (A)

5.18

Plspec
The plspec task is similar to the calcspec output instead of writing it to a table. It also such as being able to plot error bars if the information and plotting photometric results task, except that it plots its has additional capabilities, input table contains error from calcphot. In normal


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operation plspec plots synthetic spectra generated from observation mode and spectrum expressions. More than one spectrum can be plotted at a time by creating text files with one observation mode or passband on each line. The parameter vzero can also be used to substitute a set of values for variable zero ($0) in the spectra. All combinations of the observation modes, spectra, and values of vzero will be plotted. The task parameters are shown in Figure 5.26.
Figure 5.26: Plspec Parameters obsmode spectrum form (vzero (spfile (pfile (errtyp (left (right (bottom (top (append (ltype (device (wavetab (refdata = = = = = = = = = = = = = = = = Observation mode or @list Synthetic spectrum or @list Form of output graph List of values for variable zero values Spectrophotometry data Photometry data n[one] p[oint] c[ont] b[in] v[ert] h[oriz] x value for left side of graph x value for right side y value for bottom y value for top Append to existing plot? Line type: clear, solid, dashed, dotted,dotdash Graphics device Wavelength table name Reference data

" ") "none") "none") "n") INDEF) INDEF) INDEF) INDEF) no) "solid") "stdgraph") "") "")

The obsmode parameter is used to specify the desired passband to be applied to the spectral data (see Section 3.2.2). Several obsmode strings may be processed by inserting them one per line in a text file and setting obsmode=@filename. (See "Filename specifications" on page 19 for important side effects of using the @filename syntax.) If this parameter is left blank or set to "none", a default passband, equal to unity at all wavelengths, will be used. The spectrum parameter is used to specify a synthetic spectrum to be generated (see Section 3.2.3). This parameter also accepts input from list files by setting spectrum=@filename. If this parameter is left blank or set to "none", no synthetic spectra will be plotted. The form parameter specifies the desired units for the plots and photometric calculations and can be any one of the standard synphot forms: fnu, flam, photnu, photlam, counts, abmag, stmag, obmag, vegamag, jy, or mjy (see Section 3.2.4). If form is set to either counts or obmag, all quantities are multiplied by the telescope area before plotting.


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The vzero parameter contains a list of values that are substituted for variable zero ($0) wherever it appears in the spectrum expression. See Section 3.4, "Variable Substitution (VZERO)," on page 26 for a discussion of variable substitution. The spfile parameter specifies the name of a table containing spectrophotometry data, i.e., an observed spectrum. A list of one or more files can be specified using the spfile=@filename syntax. Tables are expected to have three columns labeled WAVELENGTH, FLUX, and STATERROR. The STATERROR column can be all INDEF values. If the STATERROR column is not found, an array of INDEF error values will be generated by the task. The table may also contain a FWHM column, specifying the effective instrumental resolution for each data point. If a FWHM column is not found, an array of INDEF values will be generated. The STATERROR and FWHM data may be incorporated into the plot using the errtyp parameter (see below). If an ASCII text file is used for spfile, the first through fourth columns must contain the wavelength, flux, staterror, and FWHM data. The third and fourth columns are optional. Because ASCII files cannot contain column units specifications, the wavelengths are assumed to be in Angstroms and the fluxes in units of photlam. The pfile parameter is used to specify the name of a table containing photometric data in the same format as that produced by the calcphot task. A list of files can be passed as pfile=@filename. A table file must have the column names COUNTRATE (or DATUM or FLUX for compatibility with previous versions), FORM, OBSMODE, and TARGETID. An ASCII text file must have four columns in the following order: photometric data value, form, observation mode, and target ID string. The TARGETID column is not used by this task. The data are plotted as horizontal bars, with the midpoints marked by circles. The midpoint is located at the pivot wavelength of the passband. The length of the horizontal bar is equal to the FWHM of the equivalent gaussian of the passband.


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The errtyp parameter may be used to specify how the statistical errors (if they exist) for the spectrophotometry (spfile) data should be plotted. The codes are described in Table 5.5.
Table 5.5: Error Type Codes for Plspec
Code n p b c v h Plots Error As... None (default) Plot data as points Plot data as bins (histogram) Plot +/- vertical error as continuous lines Plot vertical error bars Plot horizontal error bars

Options "v" and "h" must be used in conjunction with one of the "p", "c", or "b" options. If only "p" is selected, then the flux data will be plotted as individual points. If "v" or "h" are included along with "p", e.g., errtyp = pv, or ph, or pvh, then vertical or horizontal error bars, or both, will be plotted with each flux data point. If the "c" option is selected, two continuous lines will be plotted at values corresponding to flux + error and flux ­ error. The "ch" option will plot horizontal error bars at the location of the flux values (between the continuous lines). The "b" option will plot the flux data in bins (histogram mode). The "bv" option will overplot vertical error bars on the histogram bins. In all cases, the vertical error corresponds to the statistical error values and the horizontal error corresponds to the FWHM values read from the spfile. Individual error values that are INDEF will not be plotted. The left, right, bottom, and top parameters may be used to specify exact values for the wavelength and flux ranges to be plotted. If set to INDEF, the axes will be auto-scaled based on the combined ranges of the synthetic and observed spectral data and the photometric data. If append=yes, the results will be overplotted on an existing plot. The ltype parameter specifies the line type to be used for plotting the data. The allowed values are solid, dashed, dotted, and dotdash. The device parameter specifies the plotting device on which to produce the plot, e.g., stdgraph for on-screen display, or stdplot for hard copies. The plot that is produced will contain the following: · First, the spectral data specified by spectrum are plotted. These data are multiplied by the passband(s) specified by obsmode. If form is set to counts or obmag, the spectral data are plotted as a histogram. Data for all other form types are plotted as a continuous


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line. If variable zero ($0) is used within the spectrum parameter, the spectral data are plotted multiple times, with each curve corresponding to a different value in the vzero list. · Next, the spectrophotometry data (if any) specified via spfile will be plotted after any necessary form conversion. Error bars corresponding to the setting of errtyp will also be plotted. · Finally, photometric data read from pfile, if any, are plotted after any necessary form conversion. The passband(s) corresponding to the obsmode of the pfile data will also be plotted at the bottom of the graph. The photometry data points will be plotted as horizontal bars at a vertical location corresponding to the photometric value of the data point. The bar will be centered horizontally at the pivot wavelength and will have a width equal to the FWHM of the obsmode corresponding to that data value. Note that photometric data that are the result of a two-mode calculation, such as a color index or flux ratio of two passbands, can not be plotted because they are the result of calculations involving two passbands.

5.18.1 Examples
The first example simply plots the spectrum, in units flux calibration standard star HZ 2from our directory of spectra. Note that we leave the obsmode parameter null spectrum is not multiplied by a passband. The resulting Figure 5.27.
sy> plspec "" crcalspec$hz2_005.fits flam

of flam, of the HST calibration (" ") so that the plot is shown in


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Chapter 5: Task Descriptions Figure 5.27: Plspec Results

The second example plots a portion of the spectrum for the same star, but this time we specify the spectrum table name using the spfile parameter (leaving the spectrum parameter blank) so that we can also plot the error data from the table. We use the errtyp parameter to plot the data as individual points with vertical and horizontal bars indicating the flux uncertainties and the effective wavelength resolution for each point. Figure 5.28 shows the results.
sy> plspec "" "" flam spfile=crcalspec$hz2_005.fits \ >>> err=pvh left=2000 right=3000 top=2e-13


Plspec Figure 5.28: Results from Second Sample Plspec Run

91

The next example performs a comparison of two STIS detection modes by overplotting the countrate spectra for a B9 star in the two modes. We'll compare the g230lb grating used with the CCD detector to the g230l grating used with the NUVMAMA.We'll use the spectrum of HD 189689, star number 13 in the Bruzual-Persson-Gunn-Stryker (BPGS) atlas, and renormalize it so that it has a U magnitude of 17. Here are the (somewhat lengthy) commands to perform this:
sy> plspec stis,g230lb,ccd pgs$bpgs_13.fits,band(u),17,abmag)" counts right=3300 ltype=solid sy> plspec stis,g230l,nuvmama pgs$bpgs_13.fits,band(u),17,abmag)" counts append=yes "rn(crgridbleft=1500 "rn(crgridbltype=dotted

The results are shown in Figure 5.29.


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Chapter 5: Task Descriptions Figure 5.29: Plspec Comparison of STIS Sensitivities

The final example plots the results of some calculations made with calcphot. The integrated counts in the four WFPC2 filters F336W, F439W, F555W, and F814W were calculated for star number 23 in the BPGS atlas, renormalized to a V magnitude of 17.4. Because these filters cover disjoint wavelength ranges, genwave was used to create a wavelength table that covers the range 2800 to 11000 å, in 10 å steps. This table is called wf_wave.fits. The text file wf_filters.lis is also created, and contains the four obsmodes:
wfpc2,2,f336w,a2d7 wfpc2,2,f439w,a2d7 wfpc2,2,f555w,a2d7 wfpc2,2,f814w,a2d7

The calcphot command is as follows:
sy> calcphot @wf_filters.lis \ >>> "rn(crgridbpgs$bpgs_23.fits,band(v),17.4,vegamag)" \ >>> counts out=wf_bpgs23.fits wave=wf_wave.fits


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Now plspec is executed to plot the results:
sy> plspec "" "" counts pfile=wf_bpgs23 wave=wf_wave.fits

The resulting plot, shown in Figure 5.30, shows that the integrated count rates range from about 5 DNs per second in the F336W filter, to a maximum of about 115 DNs per second in the F555W filter. Note that the passbands plotted at the bottom have been normalized to a common maximum value.
Figure 5.30: Plotting Calcphot Results
SYNPHOT.PLSPEC

120

100

PHOT = wf_bpgs23 AREA (cm^2) = 45238.93

DETECTED COUNTS (Area-1 s-1)

80

60

40

20

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WAVELENGTH (A)

Attempting to combine these two operations (calcphot and plspec) into one execution of plspec would not produce the same type of results. For example, if we execute:
sy> plspec @wf_filters.lis \ >>> "rn(crgridbpgs$bpgs_23.fits,band(v),17.4,vegamag)" counts \ >>> wave=wf_wave.fits top=1.1

we obtain plots of the distribution of detected counts over the range of each passband, as opposed to the total integrated counts within each passband, which is what we get from calcphot (Figure 5.31).


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Chapter 5: Task Descriptions Figure 5.31: Distribution of Detected Counts
SYNPHOT.PLSPEC

1

.8

OBSMODE = @wf_filters.lis REFSPEC = rn(crgridbpgs$bpgs_23,band(v),17.4,vegamag) AREA (cm^2) = 45238.93

DETECTED COUNTS (Area-1 s-1)

.6

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5.19

Plratio
The plratio task will calculate and plot the ratio of observed spectrophotometric data to a synthetic spectrum. It can also plot the ratios of previously calculated photometric data to the same photometric data calculated from the synthetic spectrum. This task produces plots similar to those of plspec, except that it always plots the ratios of observed data (the spectrophotometric and photometric table data) to synthetic data (the combination of obsmode and spectrum). The task also computes and plots the chi-squared error of the fit, and the bias and rms errors in magnitudes. The task parameters are shown in Figure 5.32.


Plratio Figure 5.32: Plratio Parameters obsmode spectrum form spfile (pfile (vzero (left (right (bottom (top (append (ltype = (device (wavetab (refdata = = = = = none) =) = INDEF) = INDEF) = INDEF) = INDEF) = no) solid) = stdgraph) =) =)

95

Observation mode or @list Synthetic spectrum or @filename Form of output graph Spectrophotometry or @filename Photometry or @filename List of values for variable zero x value for left side of graph x value for right side y value for bottom y value for top Append to existing plot? Line type: clear,solid,dashed,dotted,dotdash Graphics device Wavelength table Reference data

Spectrophotometric ratios are plotted as histograms if form is set to counts or obmag, and as continuous lines otherwise. Photometric ratios are plotted as horizontal lines whose midpoints are marked by a circle. The x-location of the midpoint is equal to the pivot wavelength of the passband associated with the photometric value, and the length of the horizontal line is equal to the FWHM of the equivalent gaussian of the passband. The shapes of the passbands are overplotted at the base of the plot. The type of plots produced by the task is governed by the settings of the spfile and pfile parameters. If spectrophotometric ratios are not desired, spfile should be set to "none" or left blank. If photometric ratios are not desired, pfile should be set to "none" or left blank. Spectrophotometric ratios are computed for every combination of synthetic spectra and spectrophotometric files. Synthetic spectra are matched to rows in the photometric (pfile) table by matching the obsmode and spectrum parameter strings to the strings in the OBSMODE and TARGETID columns in the photometric table (see below). The strings must be exactly the same to make a match. The obsmode parameter is used to specify the desired passband to be applied to the spectral data (see Section 3.2.2). Several obsmode strings may be processed by inserting them one per line in a text file and setting obsmode=@filename. (See "Filename specifications" on page 19 for important side effects of using the @filename syntax). If this parameter is left blank or set to "none", a default passband, equal to unity at all wavelengths, will be used. Note that if photometric errors are being computed and obsmode is blank, the form parameter must be set to counts or obmag, otherwise the task cannot compute the effective stimulus of the synthetic spectrum.


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The spectrum parameter is used to specify a synthetic spectrum to be generated (see Section 3.2.3). This parameter also accepts input from list files by setting spectrum=@filename. If this parameter is left blank or set to "none", no synthetic spectra will be plotted. The form parameter specifies the desired units for the plots and photometric calculations and can be any one of the standard synphot forms: fnu, flam, photnu, photlam, counts, abmag, stmag, obmag, vegamag, jy, or mjy (see Section 3.2.4). If form is set to either counts or obmag, all computed quantities are multiplied by the HST collecting area before plotting. The vzero parameter contains a list of values that are substituted for variable zero ($0) wherever it appears in the spectrum expression. See Section 3.4, "Variable Substitution (VZERO)," on page 26 for a discussion of variable substitution. The spfile parameter specifies the name of a table containing spectrophotometry data, i.e., an observed spectrum. A list of one or more files can be specified using the spfile=@filename syntax. If the value of this parameter is set to "none" or left blank, the ratio of the spectrophotometric data to the synthetic spectra will not be plotted. In this case, the pfile parameter should have a value other than "none". Spectrophotometric tables are expected to have three columns labeled WAVELENGTH, FLUX, and STATERROR. The STATERROR column can be all INDEF values. If the STATERROR column is not found, an array of INDEF error values will be generated by the task. The table may also contain a FWHM column, specifying the effective instrumental resolution for each data point. If a FWHM column is not found, an array of INDEF values will be generated. If an ASCII text file is used for spfile, the first through fourth columns must contain the wavelength, flux, staterror, and FWHM data. The third and fourth columns are optional. Because ASCII files cannot contain column units specifications, the wavelengths are assumed to be in Angstroms and the fluxes in units of photlam. The pfile parameter is used to specify the name of a table containing photometric data in the same format as that produced by the calcphot task. A list of files can be passed as pfile=@filename. If the value of this parameter is "none" or left blank, the ratio of photometric data to the synthetic spectral data will not be plotted. A pfile table must have the column names COUNTRATE (or DATUM or FLUX for compatibility with previous versions), FORM, OBSMODE, and TARGETID. An ASCII text file must have four columns in the following order: photometric data value, form, observation mode, and spectrum (target ID) string. The task matches the photometric data to the data generated from the obsmode and spectrum parameters by the strings in the OBSMODE and TARGETID columns.


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The left, right, bottom, top, append, ltype, device, wavetab, and refdata parameters are used in the same way as described previously for the plband and plspec tasks.

5.19.1 Examples
Plot the ratio of a 15000 K blackbody spectrum to that of Vega. Since the default normalization for synthesized blackbody spectra is to set it equal to the flux of a solar radius star at a distance of 1 kpc, we first renormalize it to have the same integrated V magnitude as Vega. We also use the wavelengths listed in the alpha_lyr_stis_002 table as the wavelength grid for the calculations. The resulting ratio is plotted in units of flam.
sy> plratio "" "rn(bb(15000),band(v),0,vegamag)" flam \ >>> crcalspec$alpha_lyr_stis_002.fits wave=crcalspec $alpha_lyr_stis_002.fits left=1500 right=12000 Figure 5.33: Sample Plratio Output
SYNPHOT.PLRATIO 1.5 REFSPEC = rn(bb(15000),band(v),0,vegamag) SPHOT = crcalspec$alpha_lyr_001 RMS = 1.649343 BIAS = 1.639675 CHISQ = 40471.19 NUM PTS = 1254

1.25

Observed/Predicted

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5.20

Pltrans
The pltrans task will create photometric transformation plots such as color-color and color-magnitude diagrams. The user specifies a set of spectra, and an observing mode and form for each axis. Usually the input "spectrum" will be a file containing a list of synphot spectrum expressions or filenames. Pre-calculated photometric data can be read in from a file specified by the input parameter. Results can be saved in a table specified by the output parameter. The task parameters are shown in Figure 5.34.
Figure 5.34: Pltrans Parameters xmode ymode xform yform (vzero (input (output (left (right (bottom (top (append (mktype (device (wavetab (refdata = = = = = = = = = = = = = = = = X axis mode Y axis mode X axis form Y axis form List of values for variable zero Input table Output table x value for left side of graph x value for right side y value for bottom y value for top Append to existing plot? Marker type Graphics device Wavelength table name Reference data

) none) none) INDEF) INDEF) INDEF) INDEF) no) plus) stdgraph) ) )

The spectrum parameter is used to specify a set of synthetic spectra to be generated (see Section 3.2.3). The commands can be placed in a file, one per line, with spectrum=@filename. (See "Filename specifications" on page 19 for important side effects of using the @filename syntax). Alternatively, variable zero ($0) may be used within a single spectrum expression so that a set of spectra is generated automatically using the list of values from the vzero parameter (see below). If this parameter is left blank or set to "none", the only points plotted will be those read from the table specified by the input parameter. The xmode and ymode parameters contain obsmode strings that specify either a single passband or a color (difference of two passbands) to be calculated and plotted on the x- and y-axes of the plot. Single passbands are specified using the syntax "band(mode)", or simply "mode". Colors are specified using the syntax "band(mode1)-band(mode2)" (See "Observation Mode" on page 16.). If these parameters are set to "none" or left blank, a default observation mode that is unity at all wavelengths will be used.


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The xform and yform parameters specify the form or units for the xand y-axis data. They can be any one of the standard synphot forms: fnu, flam, photnu, photlam, counts, abmag, stmag, obmag, vegamag, jy, or mjy (see Section 3.2.4). If form is set to either counts or obmag, all computed quantities are multiplied by the HST collecting area before plotting. The vzero parameter contains a list of values that are substituted for variable zero ($0) wherever it appears in the spectrum expression. See Section 3.4, "Variable Substitution (VZERO)," on page 26 for a discussion of variable substitution. The input table contains calculated x-y pairs of data values for plotting. If the file is a FITS or STSDAS table, the x and y values are read from columns labeled FLUX1 and FLUX2, and the values of xmode, ymode, xform, and yform are read from table header keywords of the same name. The mode and form values read from the header keywords will supersede any values passed via the task parameter file. If the input file is an ASCII table, the x and y values are read from the first two columns of the table. If this parameter is set to "none" or left blank, no file will be read. The output table, if created, will have the same format as that described above for the input table. Because it has the same format as the input table, output generated by this task can be replotted later without recalculating it. If append is set to "yes" and a table of the same name already exists, the data will be appended to the existing table. If append is set to "no" and a table of the same name exists, it will be overwritten. If the value of this parameter is "none" or left blank, no file will be written. The mktype parameter specifies the marker type to be used for plotting the results. Lines, point markers, or text strings may be plotted. The recognized line types are solid, dashed, dotted, and dotdash. If a line style is chosen, a line will be plotted through the data points. The recognized point marker types are: point, fill, box, plus, cross, diamond, hline, vline, hebar, vebar, and circle. If a point style is chosen, individual markers will be plotted at each data point. Literal text strings may be plotted at each data point by setting mktype=!string (the exclamation point will not be printed with the text string). The left, right, bottom, top, append, device, wavetab, and refdata parameters function in their usual ways as described for other plotting tasks such as plband and plspec.


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5.20.1 Examples
Use pltrans to create a color-color diagram of a selection of main sequence stars contained in the BPGS spectral atlas (see Table A.8). We'll calculate and overplot two sets of colors: first the Johnson U-B and B-V colors; then the WFPC2 equivalents, F336W-F439W and F439W-F555W. The names of the tables containing the spectral data for the stars are stored in the text file bpgs_ms.lis. The Johnson colors will be plotted as plus signs, while the WFPC2 colors will be plotted as boxes. Figure 5.35 shows the results.
sy> pltrans @bpgs_ms.lis "band(b)-band(v)"\ >>> "band(u)-band(b)" vegamag vegamag bottom=-1.9 top=1.5 >>> left=-0.5 right=2.2 sy> >>> >>> >>> pltrans @bpgs_ms.lis \ "band(wfpc2,f439w)-band(wfpc2,f555w)" \ "band(wfpc2,f336w)-band(wfpc2,f439w)" \ vegamag vegamag mktype=box append+

Figure 5.35: Results from Sample Pltrans Run
SYNPHOT.PLTRANS

-1.5

-1

band(u)-band(b) (vegamag)

-.5

0

.5

1

1.5 -.5

0

.5

1

1.5

2

band(b)-band(v) (vegamag)


Refdata

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5.21

Refdata
Refdata is a parameter set (pset) and not an executable task. It defines a set of parameters that are common to most of the synphot tasks. It contains the following three parameters:
(area = 45238.93416) (grtbl = "mtab$*_tmg.fits") (cmptbl.= "mtab$*_tmc.fits") Telescope area in cm^2 Instrument graph table Instrument component table

The first, area, is the telescope collecting area, in square centimeters. The default value corresponds to the nominal 120 centimeter radius of the HST aperture. The obscuration factor of 0.86 due to the secondary is taken into account in the throughput data for the optical telescope assembly. The parameter grtbl specifies the name of the instrument graph table to be searched when interpreting obsmode strings. Similarly, the cmptbl parameter specifies the name of the component lookup table that is used to associate component keywords in the graph table with actual throughput data table names. For these last two parameters, the default string, containing the "*" wildcard character, will cause the latest available versions of the tables to be used. Invoking the refdata pset by name, i.e., typing refdata at the IRAF system prompt, will run the eparam editor on the parameter set, allowing you to modify the parameters. Alternatively, the parameters may be modified on the command line by specifying the pset name and parameter name. For example, you can type refdata.area=7853.98 to set the area to that of a 1-meter telescope. Parameters within refdata can also be modified by using eparam on any of the other synphot tasks that call for the refdata pset, e.g., by typing epar calcphot. In this case, refdata will appear as one of the calcphot task parameters. In the cl, the refdata parameter set may then be edited by positioning the cursor on the line containing the refdata name and typing ":e" to edit that pset. After editing the refdata parameters, type ":q" to indicate that you are done editing and to return to the main task parameter menu. In PyRAF, simply clicking on the refdata parameter set button will open up a new epar window that can be used to edit the values in the usual way.


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5.22

Showfiles
The showfiles task produces a list of filenames used in evaluating a synphot expression. The purpose of this task is to allow the user to better understand the results that synphot produces by listing the files that go into computing this result. There are several functions in synphot expressions which use files. The principal functions are the band and cat functions. The band function evaluates the combined throughput for an observation mode by multiplying the individual throughputs of the components in the optical path together. These component throughputs are stored in FITS tables. This task shows you the component tables that synphot uses for a specified observation mode. The cat and icat functions select a spectrum from a catalog of spectra. This task prints the name of the spectrum or spectra. This task will also print the names of files used by other functions, such as the grid, spec, and thru functions, as well as filenames embedded in the synphot expression. The showfiles task has the following two parameters:
expr = "" (refdata = "" Synphot expression Reference data

The expr parameter is an expression used by the synphot expression evaluator to compute a synthetic spectrum or passband. If the expression consists of a single call to the band function, only the arguments to the function need be given. For example, the expression "band(wfpc, f555w)" can also be given as "wfpc,f555w". The refdata parameter specifies the name of the parameter set (pset) containing the names of the instrument graph (grtbl) and component lookup (cmptbl) tables to be used by the task. This task and all other tasks in the synphot package determine the components in the optical path for a specified observing mode from the graph table. The tasks then find the corresponding FITS tables that contain the throughput data for these components by searching the component lookup table. The default values for grtbl and cmptbl in the refdata pset are set so that the most recently installed versions of each of these tables will be used.


Thermback

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5.22.1 Example
Write a list of component table names for the observing mode "acs,wfc1,f435w". The command and its output are shown below.
sy> showfiles acs,wfc1,f435w #Throughput table names: crotacomp$hst_ota_007_syn.fits cracscomp$acs_wfc_im123_004_syn.fits cracscomp$acs_f435w_004_syn.fits cracscomp$acs_wfc_ebe_win12f_005_syn.fits cracscomp$acs_wfc_ccd1_017_syn.fits

This list includes tables containing throughput (or sensitivity) data for the HST Optical Telescope Assembly (OTA), the internal imaging mirrors of the ACS, the f435w filter, the CCD dewar windows, and the CCD detector.

5.23

Thermback
This task computes the predicted thermal background flux for a specified telescope observing mode. At the user's option, it can also create an output spectrum containing the flux as a function of wavelength. Default temperatures are contained in the thermal emissivity tables (similar to the throughput tables) for each component.
obsmode =nicmos,2,f222m Instrument observation mode(s) (output =none) Output table name (tcmptb =mtab$*_tmt.fits) Instrument thermal component table (detcat=synphot$simulators/data/detectors.dat) Detector pixel scale table (wavetab = ) Wavelength table name (refdata = ) Reference data (verbose = yes) Print results to STDOUT ? (form = counts) Form for magnitude

thermback extends the usual parameterization syntax associated with the obsmode to permit the user to optionally specify a temperature associated with any component in the optical chain. For example, if the usual obsmode is nicmos,2,f222m, one can override the default temperature of the primary mirror to 300K with nicmos,2,f222m,primary#300. Legal names for specifying the components are contained in the THMODE keyword of each component emissivity file. The output table is specified by the parameter 'output'. If this parameter is set to "none" (the default) or left blank, no output table will be created. Otherwise, the task will create a table with two columns, WAVELENGTH and FLUX. The WAVELENGTH column will contain


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wavelengths in Angstroms. The FLUX column will contain the flux at the corresponding wavelengths in the specified units (counts by default). The table will also contain the header parameters GRFTABLE, OCMPTBL, TCMPTBL, and OBSMODE. These will contain the name of the graph table, the optical component lookup table, the thermal component lookup table, and the observation mode. The thermal component lookup table is specified in the tcmptb parameter. This table is analogous to refdata.cmptbl: it translates the thermal component names in the graph table to the filenames containing the emissivity tables and other relevant data for the component. For this parameter, the default string, containing the "*" wildcard character, will cause the latest available version of the table to be used. At present, CDBS only contains thermal related data files for the NICMOS instrument. thermback will generate the error "Component names not found in lookup table" for unsupported instruments. The detcat parameter specifies a file containing the pixel scale values for the HST detectors. This value is used in computing the thermal background per pixel. The wavetab parameter contains the name of the wavelength table. All flux calculations are done on the wavelength set provided by this table. If the wavetab parameter is set to "none" or left blank, a default wavelength set is computed, according to the algorithm described in Section 3.3. The refdata parameter specifies the name of the parameter set (pset) containing the names of the instrument graph (grtbl) and component lookup (cmptbl) tables to be used by the task. This task and all other tasks in the synphot package determine the components in the optical path for a specified observing mode from the graph table. This task then finds the corresponding STSDAS tables that contain the throughput and emissivity data for these components by searching the component and thermal lookup tables. The default values for grtbl and cmptbl in the refdata pset are set so that the most recently installed versions of each of these tables will be used. If the verbose parameter is set to yes, the task will print incremental results to STDOUT (usually your terminal) as it walks through the optical path and performs the thermal background calculation at each step. This can be useful to explore the individual contributions of each component to the predicted thermal background. The form parameter permits the user to specify the units for the thermal background. It is strongly recommended, however, that the default value of counts (per second per pixel) be used.


Thermback

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5.23.1 EXAMPLES
Compute the thermal background rate for the NICMOS 2 camera using the f222m filter. Store the result in table 'nic2def.fits':
sy> thermback.obsmode = "nicmos, 2, f222m" sy> thermback.output = "nic2def.fits" sy> thermback

The results are printed to STDOUT:
trate is 11.65 counts per sec per pixel

Repeat the calculation, but override the temperature of the "spider" to see what effect it would have if this component were warmer:
sy> thermback nicmos,2,f222m,spider#330

The results are printed to STDOUT, including a warning that one of the component temperatures has been overridden
Overriding spider# temperature to 330. trate is 21.13 counts per sec per pixel


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CHAPTER 6:

Inner Workings
In this chapter. . .
6.1 Syncalc / 107 6.2 Graph and Component Tables / 109

This chapter describes in detail the operation of the internal synphot expression evaluator, syncalc, as well as the structure and use of the instrument graph and component lookup tables.

6.1

Syncalc
syncalc is a function used internally by all synphot tasks. Every obsmode and spectrum parameter string used in the synphot tasks is parsed and evaluated by the spectrum expression evaluator syncalc. This expression evaluator is written to work like FORTRAN, so that the format of expressions will be easy to understand and use. Syncalc supports the four basic arithmetic operations and negation, as well as several functions. Expressions can be parenthesized in order to change the default order of evaluation. Spaces are not significant, except that the division operator must be surrounded by blanks so that it is not mistaken for part of a file name. Syncalc evaluates expressions containing file names, constants, and variables. When syncalc sees a file name, it determines if the file is a passband or a spectrum, and then reads it interpolated onto the given wavelength grid. Constants are either numbers or strings. String constants are not surrounded by quotation marks. Numeric constants are interpreted
107


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as real numbers and all mathematical operations between file names and constants are legal. Variables are represented as dollar signs followed by a positive integer; for example, $3. Variables may occur in an expression wherever a numeric constant is legal. The variable $0 is used by several tasks for looping over an expression, substituting in turn the values from the list given in the vzero parameter. The variables $1 through $9 are used by the fitting tasks. Syncalc prevents physically meaningless expressions from being computed by keeping track of the "degree" of the expression during computation. Constants, variables, and passbands have a degree of zero. Spectra have a degree of one. Each function also has an associated degree of either zero or one, depending on the result of the function. Multiplying two subexpressions yields a result whose degree is the sum of the degrees of the subexpressions. Dividing two subexpressions yields a result whose degree is the difference between the degrees of the subexpressions. Adding or subtracting two subexpressions yields a result whose degree is the same as the degrees of the subexpressions. Adding or subtracting two subexpressions that have different degrees is forbidden and causes an error exit. Negation gives a result whose degree is equal to that of the subexpression. The degree of the entire expression must be either zero or one. An expression with a degree of zero is considered to be a passband and an expression with a degree of one is a spectrum. Syncalc determines whether a file contains a passband or a spectrum by looking for a column of throughput values. If the file contains a throughput column, syncalc reads it as a passband; if not, it reads it as a spectrum. If the file is in FITS or STSDAS table format, the throughput column is identified by one of two methods: 1) the user supplies the name of the throughput column by appending it within square brackets to the end of the file name, e.g., "my_detector[dqe]"; or 2) if no column name is supplied by the user, syncalc looks for a column labeled "THROUGHPUT". Since ASCII files do not contain column names, the column number of the throughput data must be appended in square brackets to the file name, e.g., "my_detector[2]". If a column number is not supplied with an ASCII file, then the data are assumed to be a spectrum. The heart of syncalc is the set of functions that it supports. The following table lists these functions and their degree (see Section 3.2.2 and Section 3.2.3 for more details on the use and performance of these functions).


Graph and Component Tables Table 6.1: Syncalc Functions
Function band bb box cat ebmv ebmvx em gauss grid hi icat lgauss pl poly rn spec thru tilt unit z Degree 0 1 0 1 0 0 0 0 1 1 1 0 1 0 1 1 0 0 1 1 Description Telescope passband Blackbody spectrum Rectangular passband Spectrum in catalog Galactic extinction curve Extended extinction curve Gaussian emission line Gaussian passband Interpolated spectrum in grid HI continuum emission spectrum Interpolated spectrum in catalog Log gaussian passband Power-law spectrum Legendre polynomial Renormalized spectrum Spectrum file Throughput file Legendre polynomial product Constant spectrum Redshifted spectrum

109

6.2

Graph and Component Tables
Tasks in the synphot package go through the following steps when computing the combined throughput for an instrument mode:
1. The instrument mode is broken into individual keywords. Any

parameters which may be in the instrument mode are extracted.
2. The instrument graph is searched starting at the row with the lowest

innode value. All rows with this innode are examined. The row whose keyword matches one of the keywords in the instrument mode is selected. If no such row is found, the row with the keyword "default" is selected. If there is no such row, and there is only one


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row with the current innode, it is selected. Otherwise the task exits with an error.
3. Once the row is selected, the component name is saved in an array,

unless the component name is "clear". Clear components are discarded because their throughput will not modify the combined throughput.
4. The outnode of the selected row becomes the new innode and the

process of searching the graph continues until the outnode is not found in the instrument graph.
5. Once all of the component names are found in the instrument graph

table, the component lookup table is searched for the actual names of the throughput tables. The throughput values are read from the component throughput tables, resampled onto the specified wavelength set if necessary, and multiplied together to form the combined throughput. The thermback task, unlike all other synphot tasks, traverses the graph table twice: once in the usual fashion, and once to obtain the optical train necessary for thermal calculations. These trains differ because of the existence of opaque but emissive components in the optical path, such as the spider that supports the secondary mirror. The graph table is used to obtain the train of thermally emissive components in the same way it is used for optical components, except that: · obsmode keywords are compared to the thermal component name (THCOMPNAME) instead of the usual COMPNAME · Once all of the component names are found in the instrument graph table, the thermal component lookup table is searched for the actual filenames of the emissivity tables. The graph table The instrument graph table has six columns: · Component name (COMPNAME) · Instrument keyword (KEYWORD) · Input node (INNODE) · Output node (OUTNODE) · Thermal component name (THCOMPNAME) · Comment (COMMENT) The format of the instrument graph table is shown in Figure 6.1 below. The comment column is not used by synphot. It is there simply for documentation. The input and output node columns specify the light path


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111

through the HST and are used in the process of searching the graph, as explained above. Node numbers should increase as one goes down the light path in the instrument. The instrument keyword column is used to match the keywords in the instrument mode string. Sometimes a component is known by several names. It can be represented in the graph table by several rows that are identical except for the instrument keyword column, which should contain the different names that the component is known by. The component name column contains the name of the instrument component. Each component should have a unique name. The name of the component is used to link the instrument graph table to the component lookup table.
Figure 6.1: Structure of Instrument Graph Table Instrument Graph Table COMPNAME CH*20 KEYWORD CH*12 INNODE I OUTNODE I THCOMPNAME CH*20 COMMENT CH*68

The optical and thermal component lookup tables The component lookup table has four columns: · Time (TIME) · Component name (COMPNAME) · Throughput file name and column (FILENAME) · Comment (COMMENT) The format of this table is shown in Figure 6.2 below. The insertion time and comment columns are not used by the synphot tasks. The time column contains the time the component file was created. It is included for documentation and to simplify the job of delivery of new synphot tables to the Calibration Data Base System (CDBS). The time is in CDBS date-time format (yyyymmdd:hhmmss). The comment field is used solely for documentation. The component name column is used to link the instrument graph with the component name table. The throughput file and column names could have been stored directly in the graph table. However, the component throughputs are usually updated more frequently than the structure of the instrument itself (at least for HST!), so to keep from having to update the instrument graph more than is necessary, the throughput file and column names are placed in a separate table and the component name is placed in the instrument graph table. The component name column provides the link between the two tables. The file name column provides the name of the table, and optionally the


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column, of the component throughput table. The filename is the name of the binary table containing the throughput. The file name should include the directory path name. The throughput column name is placed in brackets after the file name. If there is no column name in brackets, the default column name of THROUGHPUT is used. Allowing the column name to appear in the file name column was a later enhancement to the synphot package. This modification was made in order to allow more than one throughput to be stored in a single binary table. The thermal component lookup table is identical in format to the component lookup table, except that it contains the THCOMPNAME and emissivity filename in place of the COMPNAME and throughput filename, and it does not support column names in the filename column.
Figure 6.2: Structure of Component Lookup Table Component Lookup Table TIME CH*26 COMPNAME CH*18 FILENAME CH*50 COMMENT CH*68

The throughput table The throughput table contains the component throughput as a function of wavelength. It may also contain an optional column of estimated errors or uncertainties associated with the throughput values. If the default throughput column name of THROUGHPUT is used, the error column should be named ERROR. If another throughput column name is used, the error column has the same name as the throughput column plus the suffix "_ERR". For example, if the throughput column name is DN1, the error column would be named DN1_ERR. The wavelength information is kept in a column called WAVELENGTH. The throughput table is sorted on the wavelength column in either ascending or descending order. INDEF is a legal value for the throughput or error columns and indicates that the throughput is not known at that wavelength. The wavelength column, however, should never have a value of INDEF. All columns in the throughput table should contain 32-bit floating-point numbers. The units must be specified for the wavelength column. The synphot tasks use Angstroms internally; however, the wavelength units may be Angstroms, nanometers, microns, millimeters, centimeters, meters, hertz, kilohertz, megahertz, gigahertz, eV, KeV, or MeV. Any unique abbreviation of the preceding units is also allowed. The throughput and error column units may be blank, however the following units are allowed for documentation: transmission, qe, or dn/photon. As with the wavelength units, any unique abbreviation is allowed.


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113

A component throughput may also be parameterized, meaning that the throughput is a function of some other variable besides wavelength. An example of parameterized components are the WFPC2 ramp filters. The throughput of these filters varies as a function of position on the filter. The throughput table for a parameterized component contains several throughput and error columns, evaluated at different values of the parameter. The synphot package interpolates between these columns when computing the throughput for a given value of the parameter. The column name is a root name followed by one or more parameter values. Each parameter is preceded by a hash mark (#). The parameter values are those at which the column is evaluated. For example, suppose a ramp filter is parameterized on its peak wavelength, which varies between 3500 and 4000 å. If the throughput is evaluated at intervals of 100 å, the throughput column names would be WFPC2_RAMP#3500, WFPC2_RAMP#3600, ... WFPC2_RAMP#4000. The error column associated with each of these throughputs has the suffix "_ERR" added to the root name. The name of the error columns for the ramp filters in the previous example would be WFPC2_RAMP_ERR#3500 ... WFPC2_RAMP_ERR#4000. Entries in the graph and component tables indicate that the component is parameterized by containing one or more hash marks. The number of hash marks indicates how many parameters the component takes. To continue with the previous example, the keyword column in the graph table might contain the value RAMP# and the filename column in the component lookup table might contain the name "wfpc2_ramp[ramp#]". Parameterized components can be placed in the same throughput table as other components. The thermal emissivity table The thermal emissivity table contains the component emissivity as a function of wavelength. It may also contain an optional column of estimated errors or uncertainties associated with the emissivity values. The column names should be WAVELENGTH, EMISSIVITY, and ERROR. Restrictions on wavelength values, units, and numerical formats are the same as for the component table.
Table 6.2: Thermal Emissivity Table. BEAMFILL DEFT THTYPE THCMPNAM THMODE = 1. = 77. ='THRU' = 'nic2_f110w' = 'f110w' / / / / / Fraction of beam filled by this component Default temperature in kelvins Thermal type (opaque/thru/numeric/clear) Name of thermal component Keyword in obsmode to specify temperature


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Chapter 6: Inner Workings Table 6.3: The emissivity table also contains some crucial information in

header keywords:
BEAMFILL= 1. DEFT = 77. THTYPE ='THRU' THCMPNAM='nic2_f110w' THMODE ='f110w' / / / / / Fraction of beam filled by this component Default temperature in kelvins Thermal type (opaque/thru/numeric/clear) Name of thermal component Keyword in obsmode to specify temperature

BEAMFILL specifies the fraction of the optical beam filled by this component. This value is usually one, but it depends on the precise optical layout of the instrument. DEFT specifies the default temperature of the component, in Kelvins. This is the temperature that will be used in the thermal calculations unless it is overridden in the obsmode. THTYPE specifies the type of thermal component that is described by this file. Opaque components are those which partially obstruct the beam: they emit, but do not pass, radiation. Thru components are those which have both throughput and emissivity: all the usual optical elements are of this sort. Numeric elements are those components which do not correspond to a physical device in the instrument, but are represented as such for convenience, such as the detector quantum efficiency. Clear elements are those which do not contribute to either throughput or emission: usually this value is associated only with rows in the graph table that organize the flow. THCOMPNAME and THMODE are the associated pair of values used when traversing the graph table. THMODE contains the obsmode keyword which points to the associated THCOMPNAME. The usual keyword# parameterization syntax is overridden for use with the thermal emissivity tables. Instead, this syntax is used to specify a component temperature (overriding the default temperature present in the DEFT header keyword).


CHAPTER 7:

Calibration Using Synthetic Photometry
In this chapter. . .
7.1 Principles of calibration / 115 7.2 Accuracy and errors in synthetic photometry / 118

7.1

Principles of calibration
Spectrophotometric data taken with modern array detectors are simpler to calibrate than broadband photometry because the spectrophotometric pixels have very narrow passbands across which the detector sensitivity, atmospheric extinction, and standard star continuum are effectively constant. The number of detected counts per exposure time t in a pixel at wavelength covering the wavelength interval is given by: C() ----------- = A P ( ) f ( ) ----- (counts/sec) hc t where A is the nominal collecting area of the telescope, f() is the flux density of the target star, P() is the dimensionless bandpass throughput function, and the division by h = hc / converts the energy flux to a photon flux as is appropriate for photon-counting detectors. To calibrate, we want to determine the unit response curve U(), which gives as a function of wavelength the factor that converts observed count rate to source flux density. U() is determined from observed count rate spectra of spectrophotometric standard stars whose absolute flux spectra are known, and can
115


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then be used to convert count rate spectra observed on other targets to absolute fluxes. Typically, this is done by dividing the known spectrum of a standard star by its observed count rate spectrum, so that U() is given by: f ( ) hc / A U ( ) = --------------------- = -----------------------------P() C() / t (ergs/cm /å)
2

Once U() is determined, the absolute flux distribution of any observed source can be computed by simply multiplying the source's count rate spectrum, C()/ t, by U(): f ( ) = U ( ) C ( ) / t (ergs/sec/cm /å) Synthetic photometry permits a precise generalization of this procedure from the narrow passbands of spectrophotometric pixels to a passband P() of arbitrary width and shape. For a broadband photometric mode the analogous expression giving the detected count rate through passband P is: A C(P) ------------ = ----- P ( ) f ( ) d hc t The precise definition of mean flux density in a broad passband must then be: P ( ) f ( ) d ---------------------------------------f ( P ) = P() d so the count rate to flux density conversion factor for a broad passband is: f ( P ) hc / A U ( P ) = --------------------- = -------------------------C(P) / t P() d The calibration procedure for broadband photometry is now essentially parallel to that for spectrophotometry. The only difference is that in the spectrophotometric case the source's flux distribution can be considered constant across the narrow bandwidth of each spectroscopic pixel, whereas in the photometric case the integral over wavelength must be performed more carefully. So the normal method of calibrating photometric modes is to first calculate the mean flux densities of spectrophotometric standard stars in the broad bands, using the known flux spectra and passband shapes, and then derive the flux conversion factors U(P) by comparing the mean flux densities against the corresponding observed count rates. Notice, however, that the last equation above shows us that, if we know the passband function P(), we can derive U(P) directly, without the need
2


Principles of calibration

117

for standard star observations. This is the technique used by synphot (and incorporated into the WFPC2, ACS calibration pipelines) to calibrate HST observing modes. The value of the PHOTFLAM header keyword that appears in calibrated WFPC2, ACS, and STIS images is the flux conversion factor U(P), computed directly from the passband function of the observation mode. Once known, the flux conversion factor can be used to express the count rate observed on an unknown target to the precise flux density of that target, so that for an observed number of counts C in an exposure time of t, the corresponding mean flux density within the passband is simply: f ( P ) = U ( P ) C / t Corresponding magnitudes are given by: m ( P ) = ­ 2.5 log ( U ( P ) C / t ) + K where K is chosen for convenience to be ­21.10 (for U in units of ergs cm-2 å-1) so that m (5500 å) is approximately equal to the Johnson V magnitude. A potential difficulty arises in the conversion between f(P) and f(P), since it is not at first obvious from their definitions that their relationship is independent of the source spectrum. Fortunately, such conversions can be made precisely by the relation c f ( P ) = f ( P ) ---------------2 P ( P ) where P (P) is the passband's pivot wavelength. This parameter is sourceindependent and defined as P ( P ) =

P ( ) d ----------------------------- P() d /

The HST magnitude system, based on f, can then be converted to an analogous f (ergs cm-2 s-1 Hz-1) system by calculating m ( P ) = m ( P ) ­ 5 log P ( P ) + 18.70 where P is the pivot wavelength of the passband in Angstroms; m will then be approximately equal to AB from the ground-based optical AB79 system of Oke and Gunn (1983). It is important to use the pivot wavelength when making this conversion, since a 1% wavelength error would cause a 5% error in the converted broadband flux.


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For any non-zero passband width, the pivot wavelength differs somewhat from the more traditional average wavelength,

P() d 0 = ---------------------------P() d
which is also source-independent. As a measure of the width of a passband we can use the rms width



rms

=

( ­ 0 ) P ( ) d --------------------------------------------- P()d

2

All of these source-independent characteristics can be computed for a given passband using the bandpar task in the synphot package. The pivot wavelength, average wavelength, and rms width are known as "pivwv", "avglam", and "bandw", respectively. It is also useful to define a source-dependent passband parameter that can be used to estimate shifts of the effective wavelength with source characteristics (e.g., temperature, reddening, redshift, etc.). We define the effective wavelength as the mean wavelength of the detected photons,
eff

f ( ) P ( ) d = --------------------------------------------f ( ) P ( ) d

Since this is a source-dependent parameter, it is calculated by calcphot (because bandpar and calcband, by definition, only support passband data and not spectral data), where it is referred to as "efflam".

7.2

Accuracy and errors in synthetic photometry
The accuracy of synphot results depends on the accuracy of the zero points and the shapes of the sensitivity curves for each bandpass in the database. In particular, zero point issues arise whenever one compares synthetic photometry to real photometry. Of course, the accuracy also depends on the spectrum or model used for the calculation.


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7.2.1 Groundbased photometric systems
synphot supports a number of groundbased photometric systems, including Johnson, Cousins, Bessell, SDSS, and more. Each of these standard systems comes with its own set of corrections for airmass, for objects of extreme color, and so on. Accurate calibrations of groundbased data can only be achieved by measuring photometric standard stars along with the object(s) of interest, and performing your own measurement of the zero point offsets. Ground-based U band photometry is particularly problematic, as the short-wavelength side of its bandpass cutoff is determined by atmospheric conditions. For more detail on calibrating groundbased photometry, see for example Bessel et al, 1998 (UBVRIJHKL system) and Cohen et al, 2004 (2MASS JHK system). "As the standard systems have been established from natural system colors using linear and non-linear corrections of at least a few percent, we should not be reluctant to consider similar corrections to synthetic photometry to achieve good agreement with the standard system across the whole temperature range of the models." Bessell et al, 1998

7.2.2 Vegamags
synphot offers the option of producing photometry in units vegamags, defined such that Vega has magnitude zero in all passbands. accomplish this transformation, the passband integral is calculated first the source spectrum and then again for the spectrum of Vega built into system. The ratio of the two results is converted to a magnitude. of To for the

The magnitude of Vega in "vegamags" is defined to be zero in all passbands, even if the real value is known to be different. (e.g., Vega = 0.026 mags in Johnson V

Naturally the accuracy of such results depends on the accuracy of the Vega spectrum used. As of October 2004, the Vega spectrum in the synphot system is a composite flux standard (Bohlin & Gilliland 2004) which consists of IUE data from 1255-1675A, STIS CCD fluxes from 1650-4200A (Bohlin & Gilliland 2004), and a specially tailored Kurucz model longward of 4200A and from 900-1255A (Kurucz 2003).


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7.2.3 HST bandpasses
The bandpasses for HST instruments are more stably defined than those of groundbased systems, for several reasons. HST bandpasses are instrumental bandpasses, defined by a single specific combination of telescope/detector/filter hardware. There are of course no variations in atmospheric conditions such as air mass and humidity, which affect the sensitivity of groundbased instruments. Temperature conditions on orbit are also extremely stable, and sets of standard stars are routinely observed for calibration purposes. However, care must still be taken when attempting accurate calibrations. Discussions of the photometric zero points and stability for each of the instruments can be found in the relevant sections of the HST Data Handbook. Detailed information can also be found for ACS in DeMarchi et al, 2004; for NICMOS and STIS in Bohlin et al, 2001; and for WFPC2 in Heyer et al, 2004.


APPENDIX A:

On-Line Catalogs and Spectral Atlases
In this appendix . . .
A.1 HST Calibration Spectra A.2 Kurucz 1993 Atlas of Model Atmospheres A.5 Bruzual Spectrum Synthesis Atlas A.6 Gunn-Stryker Spectrophotometry Atlas A.7 Bruzual-Persson-Gunn-Stryker Spectrophotometry Atlas A.8 Jacoby-Hunter-Christian Spectophotometry Atlas A.9 Bruzual-Charlot Atlas A.10 Kinney-Calzetti Atlas A.11 Buser-Kurucz Atlas of Model Atmospheres A.12 AGN Atlas A.13 Galactic Atlas / / / / / / / / / / / 122 125 131 132 132 135 138 139 139 142 142

There are several spectral atlases consisting of both observed and model data that are available in FITS table format for use with synphot. These are available at STScI on all science computing clusters in the crrefer directory areas. Off-site users can obtain these data via anonymous ftp on the node ftp.stsci.edu where they are located in several subdirectories under the /cdbs directory. Current descriptions and access to all available calibration spectra and astronomical catalogs can also be found at the CDBS web site, which is updated more frequently than this manual:
http://www.stsci.edu/hst/observatory/cdbs/astronomical_catalogs.html.

The subdirectories /cdbs/calspec/ and /cdbs/grid/ contain the data tables for all of the atlases described here. For easy access from the synphot tasks, the on-line directories containing the various atlases are defined via environment variables within STSDAS. All subdirectories are defined relative to the crrefer$ directory environment variable, which is
121


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set in the IRAF file hlib$extern.pkg. Off-site users should define crrefer in this file to point to the local directory area that contains the atlas tables. The environment variables crcalspec$, crgridbk$, crgridbpgs$, crgridbz77$, crgridgs$, and crgridjac$ are subsequently defined in the STSDAS file stsdaslib$zzsetenv.def to point to subdirectories beneath crrefer$ which contain the spectral data tables for each of the individual atlases.

A.1 HST Calibration Spectra
The directory crcalcspec$ contains the composite stellar spectra that are the fundamental flux standards for HST calibrations. All files are in machine independent binary FITS table format. Information about the pedigree of a given spectrum is in the header of the FITS table file, which can be read with the IRAF hedit task or examined usying pyFITS. In some cases, the spectrum is truncated in the blue (or in the red) at wavelength longer (shorter) than the sensitivity limit of the instrument. As a result, synphot may underestimate the total counts. Users should check that the wavelength range of the spectrum/model they are using is compatible with the wavelength range of the calculation they require. Table A.1 below summarizes the set of recommended standard star spectra. Columns 2 and 3 give the V and B magnitudes of the stars. More documentation on these stars, e.g. coordinates, finding charts and spectral types can be found in Turnshek et al. (1990), Bohlin, Colina & Finley (1995), and Colina & Bohlin (1997). Column 4 is the computer compatible file name with the plus and minus signs converted to underscores. Thus, the actual CALSPEC file name is the prefix in column 4, plus one of the suffixes in columns 5-8, plus ".fits". For example, a standard that has STIS data is "bd_28d4211_stis_001.fits". These spectra can be used with synphot tasks by setting either the spectrum or spfile task parameters to the name of the desired file, e.g., crcalspec$alpha_lyr_stis_002.fits. The unit of flux in all files is erg s-1 cm-2 A-1. The pure hydrogen WD model LTE spectra of Bohlin (2000) have been replaced by Hubeny NLTE models calculated with his Tlusty code (Bohlin 2003). These fundamental standards GD71, GD153, G191B2B, and HZ43 are listed by Calibration Data Base System (CDBS) suffix in column 5 of the Table and provide the basis for the secondary flux standards. The observational spectra from columns 5-8 can be compared with the models;


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123

and in the case of G191B2B, there is ultraviolet line blanketing at the few percent level. The model calculations extend to 30 microns and cover the long wavelength limits of 2.7 microns for NICMOS, 1.1 microns for STIS and ACS, and 27 microns for JWST. Vega was observed by STIS (Bohlin & Gilliland 2004); and the new composite flux standard alpha_lyr_stis_002.fits consists of IUE data from 1255-1675A, STIS CCD fluxes from 1650-4200A, and a specially tailored Kurucz model longward of 4200A (Kurucz 2003) and from 900-1255A. Column 6 lists the 20 CDBS suffix names for the second choice standard stars with STIS data from Bohlin, Dickinson, & Calzetti (2001). Tabulated in column 7 are the next best standard star flux distributions, which are composed of FOS spectra in the UV and Oke spectra at the longer wavelengths. Also appearing in column 7 are the three solar analogs that are comprised of FOS observation but do not have "_FOS" in the CALSPEC file name. The names for the last, but largest, set of standard stars appear in column 8 of the Table. The application of corrections to the original IUE and optical fluxes produces a consistent set of spectrophotometric standards from 1150 to 9200A (Bohlin 1996 and references therein). This set of standards is composed of IUE+Oke data only. CALSPEC also contains the ultraviolet to near-infrared absolute flux distribution of the Sun (filename: sun_reference_stis_001.fits) to 2.7 microns, which is used to model the IR spectrum of the three solar analog stars. The solar reference spectrum combines absolute flux measurements from satellites and from the ground with a model spectrum for the near-infrared (Colina, Bohlin, & Castelli 1996). The SUPPLEMENTAL_CALSPEC directory contains previous CALSPEC versions and spectrophotometry that may be useful for special purposes. The order of preference for the choice of a standard flux distribution is from left to right in the Table A.1, i.e. from the best in column 5 to the last choice with the lowest quality in column 8. Table A.2 contains the spectral type of some of the HST calibration sources.


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Star name (1) AGK+81D266 ALPHA-LYR BD+25D4655 BD+28D4211 BD+33D2642 BD+75D325 FEIGE110 FEIGE34 FEIGE66 FEIGE67 G191B2B G93-48 GD108 GD153 GD50 GD71 GRW+70D5824 HD93521 HZ21 HZ2 HZ43 HZ43B HZ44 HZ4 LB227 LDS749B LTT9491 NGC7293

V (2) 11.94 0.03 9.69 10.51 10.83 9.55 11.83 11.18 10.51 11.82 11.77 1 2.74 13.56 13.35 14.06 13.03 12.77 6.99 14.69 13.88 12.91 14.30 11.67 14.51 15.32 14.68 14.10 13.53

B-V (3) -0.34 0.00 -0.31 -0.34 -0.17 -0.33 -0.30 -0.34 -0.29 -0.34 -0.33 -0.01 -0.22 -0.29 -0.28 -0.25 -0.09 -0.27 -0.33 -0.09 -0.31 ... -0.29 +0.09 +0.06 -0.04 +0.03 -0.37

CDBS name (4) agk_81d266 alpha_lyr bd_25d4655 bd_28d4211 bd_33d2642 bd_75d325 feige110 feige34 feige66 feige67 g191b2b g93_48 gd108 gd153 gd50 gd71 grw_70d5824 hd93521 hz21 hz2 hz43 hz43b hz44 hz4 lb227 lds749b ltt9491 ngc7293

Model (5)

STIS (6) _STIS_001 _STIS_002

FOS+Oke (7)

IUE+Oke (8) _005 _004 _002

_STIS_001

_FOS_003 _FOS_003

_005 _004 _005 _005 _005 _002 _002

_STIS_001 _STIS_001 _STIS_001

_FOS_003

_MOD_004

_STIS_001

_FOS_003

_005 _004 _005

_MOD_004

_STIS_001

_FOS_003 _004

_MOD_005

_STIS_001 _STIS_001 _STIS_001 _STIS_001

_FOS_003 _005 _005 _005 _005

_MOD_004

_STIS_001 _STIS_001 _STIS_001 _STIS_001

_FOS_003

_FOS_003

_005 _004 _004 _005 _002 _005

P041C P177D P330E SUN

12.00 13.47 13.00 -26.75

0.62 0.66 0.64 0.63

p041c p177d p330e sun_reference

_STIS_001 _STIS_001 _STIS_001 _STIS_001

_001 _001 _001

(1) The unit of flux in all files is erg s-1 cm-2 A-1.


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125

Star

Type

AGK +81 266 alpha Lyra BD +28 4211 BD +33 2642 BD +75 0325 Feige 34 Feige 110 G93-48 G191-B2B GD50 GD108 GRW +70 5824 HD 93521 HZ 2 HZ 4 HZ 21 HZ 44 LB 227 LDS 749B NGC 7293

sdO A0 V Op B2 IV O5p DO D0p DA3 DA0 DA2 sdB? DA3 O9 Vp DA3 DA4 DO2 sdO DA4 DB4

A.2 Kurucz 1993 Atlas of Model Atmospheres
The atlas contains about 7600 stellar atmosphere models for a wide range of metallicities, effective temperatures and gravities. These new LTE models have improved opacities and are computed with a finer wavelength and temperature resolution than the previous Buser-Kurucz atlas installed in the CDBS (crgridbk). The micro-turbulent velocity is 2 km s-1. The new atlas installed in the CDBS is from the Kurucz database at Goddard Space Flight Center. The original atlas (CD-ROM No. 13) was created on August 22, 1993 and can be obtained from Dr. R. Kurucz. The atlas includes models of abundances (log_Z) relative to solar of +1.0, +0.5, +0.3, +0.2, +0.1, +0.0, -0.1, -0.2, -0.3, -0.5, -1.0, -1.5, -2.0, -2.5,-3.0, -3.5, -4.0, -4.5, and -5.0. The grid of models cover the gravity range from log_g= 0.0 to +5.0 in steps of +0.5. The range in effective


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temperature from 3500 K to 50000 K is covered with an uneven grid (see Table A.3). The model spectra cover the ultraviolet (1000A) to infrared (10 microns) spectral range with non-uniform wavelength spacing (see Table A.4). Table A.3: Grid of temperatures for the models
Temperature Range K 3000 - 10000 10000 - 13000 13000 - 35000 35000 - 50000 Grid Step K 250 500 1000 2500

Table A.4: Wavelength coverage for the models
Wavelength Range microns 0.10 - 0.29 0.29 - 1.00 1.00 - 1.60 1.60 - 3.20 3.20 - 8.35 8.35 - 10.0

Grid Step A 10 20 50 100 200 400

A.3 THE HST/CDBS VERSION OF THE 1993 KURUCZ ATLAS
The atlas is divided in 19 independent subdirectories, according to metallicity. Within each subdirectory the stellar atmosphere models are given in STDAS multicolumn table format. Each table consist of 12 different columns, the first one containing the wavelength grid and each of the rest containing the spectrum of a star with the same effective temperature but different gravity, ranging from log_g= 0.0 to +5.0. Columns filled with zeros indicate that the model spectrum for that particular metallicity, effective temperature and gravity combination is not covered by the atlas.


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127

The names of the table files are given as kszz_ttttt.fits where "k", for Kurucz, is the first letter of the atlas; "szz" is the metallicity of the model (zz) with its sign (s); and "ttttt" is the model's effective temperature, using four or five digits depending on the value. For instance, models for an effective temperature of 5000 K with log_Z= -0.5 and log_Z= +3.5 are indicated by ttttt= 5000, s= m, zz= 05 and ttttt= 5000, s= p, zz= 35, i.e. km05_5000.fits and kp35_5000.fits. Within each individual table file, each column is named "gyy" where "yy" corresponds to 10*log_g. For example, log_g= +0.5 and log_g= +4.0 models are located in columns named g05 and g40, respectively. See Table A.5 for an example of a standard header of a table file. In this example the name of the file is kp00_8000.fits and contains all the models for a star of metallicity log_Z= 0.0 and effective temperature Teff= 8000 K. Models cover a range of gravities from log_g= +1.0 (g10 in the header) to log_g= +5.0 (g50 in the header). Models for gravities log_g= +0.0 and +0.5 are not available for this particular metallicity and effective temperature combination, and therefore do not appear listed in the header. Their corresponding columns (g00 and g05) are filled with zeros. The models are in FLAM surface flux units, i.e. ergs cm-2 s-1 A-1.


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Appendix A: On-Line Catalogs and Spectral Atlases Table A.5: Sample FITS Header from Kurucz 93 Model
SIMPLE = BITPIX = NAXIS = EXTEND = COMMENT COMMENT COMMENT COMMENT ORIGIN = FILENAME= TEFF = LOG_Z = HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY HISTORY END T / file does conform to FITS standard 16 / number of bits per data pixel 0 / number of data axes T / FITS dataset may contain extensions FITS (Flexible Image Transport System) format defined in Astronomy and Astrophysics Supplement Series v44/p363, v44/p371, v73/p359, v73/p365. Contact the NASA Science Office of Standards and Technology for the FITS Definition document #100 and other FITS information. 'STScI-STSDAS/TABLES' / Tables version 1999-03-22 'kp00_8000.fits' / name of file 8000 0.00000000000000E+00 g10 g15 g20 g25 g30 g35 g40 g45 g50 Kurucz model atmospheres (1993) Fluxes tabulated in units of erg/s/cm^2/A are surface fluxes. To transform to observed fluxes multiply by (R/D)^2 where R is the radius of the star and D the distance. Each column in the table represents the spectrum of a star for the same metallicity and effective temperature but different gravity.

Physical fluxes of the spectra are given in FLAM surface flux units, i.e. ergs cm-2 s-1 A-1. These flux units differ from those in the Kurucz CD-ROM by a factor of 3.336 x 10-19 x lambda2 x (4pi)-1, i.e. are converted from ergs cm-2 s-1 Hz-1 steradian-1 to ergs cm-2 s-1 A-1. To convert to observed flux at Earth, multiply by a factor of (R/D)2 where R is the stellar radius, and D is the distance to Earth. The names of the files located in each metallicity subdirectory are listed in the README file located in each subdirectory. The range in gravity covered by the models for the different temperatures is also indicated.


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129

A.4 USE OF KURUCZ ATLAS WITH SYNPHOT
Synphot tasks now permit the use of spectra selected from one of many columns in a single STSDAS table file. One does this by specifying as the "spectrum" parameter the name of the disk file (as before), and appending the name of the column containing the flux in brackets. Thus, to select any model spectrum characterized by a given metallicity, effective temperature, and gravity, specify a "spectrum" of the form: crgridk93$m_directory/kszz_ttttt.fits[gyy], where m_directory is the name of the subdirectory for a given metallicity. For example, to select the spectrum of a star with a metallicity of +0.1, a temperature of 10,000 K, and log gravity of 3.0, the specification would be: crgridk93$kp01/kp01_10000.fits[g30]. Alternatively, one may select a model spectrum within a synphot expression using the function icat (which interpolates between the nearest matching models) or cat (which simply selects the closest match). The syntax for the Kurucz models is icat(k93models,Teff,metallicity,logG). See section 5.3.1 for an example that includes the use of this function. The icat task can give incorrect results without warning if it is used at the edges of the defined grid of models. See above for a discussion of the available ranges for these values, and exercise caution when selecting a value near one of the extremes. Please note that the model spectra in the atlas are in surface flux units. Thus, if the number of counts or the calculated absolute flux is needed, the model spectrum must be renormalized appropriately. One can do this in synphot with the "rn" function. Since the entire atlas occupies close to 70MB of disk space, many applications could be satisfied by a copy of the solar metallicity spectra, only. A list of solar metallicity stars of different spectral types and luminosity classes together with their closest Kurucz model spectrum is presented in Table A.6. The physical parameters, Teff and log_g, characterizing each star are taken from Schmidt-Kaler's compilation of physical parameters of stars (Schmidt-Kaler 1982, Landolt-Bornstein VI/2b). The U-B and B-V colors of the closest model agree with the characteristic color of each star (see Schmidt-Kaler 1982) to better than 0.06 magnitude.


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Appendix A: On-Line Catalogs and Spectral Atlases Table A.6: Suggested models for specific stellar types
Type O3V O5V O6V O8V B0V B3V B5V B8V A0V A5V F0V F5V G0V G5V K0V K5V M0V M2V M5V B0III B5III G0III G5III K0III K5III M0III O5I O6I O8I BOI B5I AOI A5I F0I F5I G0I G5I K0I K5I M0I M2I T_{eff} 52500 44500 41000 35800 30000 18700 15400 11900 9520 8200 7200 6440 6030 5770 5250 4350 3850 3580 3240 29000 15000 5850 5150 4750 3950 3800 40300 39000 34200 26000 13600 9730 8510 7700 6900 5550 4850 4420 3850 3650 3450 log_g +4.14 +4.04 +3.99 +3.94 +3.9 +3.94 +4.04 +4.04 +4.14 +4.29 +4.34 +4.34 +4.39 +4.49 +4.49 +4.54 +4.59 +4.64 +4.94 +3.34 +3.49 +2.94 +2.54 +2.14 +1.74 +1.34 +3.34 +3.24 +3.24 +2.84 +2.44 +2.14 +2.04 +1.74 +1.44 +1.34 +1.14 +0.94 +0.34 +0.14 -0.06 Kurucz model kp00_50000[g50] kp00_45000[g50] kp00_40000[g45] kp00_35000[g40] kp00_30000[g40] kp00_19000[g40] kp00_15000[g40] kp00_12000[g40] kp00_9500[g40] kp00_8250[g45] kp00_7250[g45] kp00_6500[g45] kp00_6000[g45] kp00_5750[g45] kp00_5250[g45] kp00_4250[g45] kp00_3750[g45] kp00_3500[g45] kp00_3500[g50] kp00_29000[g35] kp00_15000[g35] kp00_5750[g30] kp00_5250[g25] kp00_4750[g20] kp00_4000[g15] kp00_3750[g15] kp00_40000[g45] kp00_40000[g45] kp00_34000[g40] kp00_26000[g30] kp00_14000[g25] kp00_9750[g20] kp00_8500[g20] kp00_7750[g20] kp00_7000[g15] kp00_5500[g15] kp00_4750[g10] kp00_4500[g10] kp00_3750[g05] kp00_3750[g00] kp00_3500[g00]


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131

A.5 Bruzual Spectrum Synthesis Atlas
Gustavo Bruzual has provided 77 stellar spectra frequently used in synthesis of galaxy spectra. They are available in directory crgridbz77$ and are stored in 77 individual tables called bz_nn.fits, where nn runs from 1 to 77. A list of the file names and spectral types is shown in Table A.7. Table A.7: Bruzual Synthetic Spectral Atlas
File
bz_1 bz_2 bz_3 bz_4 bz_5 bz_6 bz_7 bz_8 bz_9 bz_10 bz_11 bz_12 bz_13 bz_14 bz_15 bz_16 bz_17 bz_18 bz_19 bz_20 bz_21 bz_22 bz_23 bz_24 bz_25 bz_26 bz_27 bz_28 bz_29 bz_30

Type
O5 O7 O8 O9 B0 B1 B2 B3 B5 B7 B8 B9 A0 A1 A2 A3 A5 A7 F2 F5 F6 F7 F8 G0 G1 G2 G5 K0 K3 K5 V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V

File
bz_31 bz_32 bz_33 bz_34 bz_35 bz_36 bz_37 bz_38 bz_39 bz_40 bz_41 bz_42 bz_43 bz_44 bz_45 bz_46 bz_47 bz_48 bz_49 bz_50 bz_51 bz_52 bz_53 bz_54 bz_55 bz_56 bz_57 bz_58 bz_59 bz_60

Type
K9 V M0 V M1 V M2 V M6 V O8 III O9 III B0.5 III B1 III B2 III B5 III B7 III B8 III B9.5 III A0 III A2 III A3 III A5 III A7 III F0 III G0 III G8 III G9 III K0 III K2 III K5 III K6 III M0 III M1 III M3 III

File
bz_61 bz_62 bz_63 bz_64 bz_65 bz_66 bz_67 bz_68 bz_69 bz_70 bz_71 bz_72 bz_73 bz_74 bz_75 bz_76 bz_77

Type
M4 III M5 III M6 III O7 I O9.5 I B0 I B0.5 I B5 I B8 I A2 I F0 I F2 I F8 I G0 I G2 I G8 I M1M2 I


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A.6 Gunn-Stryker Spectrophotometry Atlas
This is an optical spectrophotometric catalog of 175 stars covering a complete range of spectral types and luminosity classes from the observations of Gunn and Stryker (1983). The spectra cover the wavelength range 3130 to 10800 å and are located in the directory crgridgs$. The list of stars contained in this atlas is identical to the BPGS atlas, and are shown in Table A.8. Note that when referring to Table A.8 for the names of files in the Gunn-Stryker atlas, the names are of the form gs_nnn.fits, instead of bpgs_nnn.fits.

A.7 Bruzual-Persson-Gunn-Stryker Spectrophotometry Atlas
This is an extension of the Gunn-Stryker optical atlas where the spectral data have been extended into both the UV and the infrared. They are available as 175 STSDAS tables in the directory crgridbpgs$. The IR data are from Strecker et al. (1979) and other unpublished sources. The IR and optical data were tied together by the V­K colors. Note that the spectral data for all of the stars in this atlas have been arbitrarily renormalized to a V magnitude of zero. Therefore in order to use these data for calculations of absolute photometry they must be renormalized to their appropriate absolute levels. The magnitudes in this atlas are magnitudes and observed spectra and colors stored in header keywords in each of the tables not on the standard UBVRI system. They are "scanner" colors that were synthesized by the authors from the (see Gunn and Stryker 1983).


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133

The file names, star names, and spectral types for the BPGS atlas are listed in Table A.8..
Table A.8: Bruzual-Persson-Gunn-Stryker Spectral Atlas File bpgs_1 bpgs_2 bpgs_3 bpgs_4 bpgs_5 bpgs_6 bpgs_7 bpgs_8 bpgs_9 bpgs_10 bpgs_11 bpgs_12 bpgs_13 bpgs_14 bpgs_15 bpgs_16 bpgs_17 bpgs_18 bpgs_19 bpgs_20 bpgs_21 bpgs_22 bpgs_23 bpgs_24 bpgs_25 bpgs_26 bpgs_27 bpgs_28 bpgs_29 bpgs_30 bpgs_31 bpgs_32 bpgs_33 bpgs_34 Star 9 SGR 9 SGE HR 8023 BD -01 0935 60 CYG 102 HER ETA HYA IOTA HER HR 7899 38 OPH HR 7174 9 VUL HD 189689 THETA VIR NU CAP HR 6169 HD 190849A 69 HER HD 190849B 58 AQL 78 HER HR 6570 HD 187754 THETA1 SER PRAESEPE 276 PRAESEPE 114 PRAESEPE 154 HD 190192 PRAESEPE 226 PRAESEPE 37 HD 191177 PRAESEPE 332 BD +29 3891 PRAESEPE 222 F6 V F4 V A5 V Type O5 O8 F O6 B1 V B1 V B2 V B3 V B3 V B4 V A1 V B6 V B7 V B9 V A0 V B9 V A2 V A1 V A2 V A3 V A0 V B9 V A7 V A2 V A5 V File bpgs_35 bpgs_36 bpgs_37 bpgs_38 bpgs_39 bpgs_40 bpgs_41 bpgs_42 bpgs_43 bpgs_44 bpgs_45 bpgs_46 bpgs_47 bpgs_48 bpgs_49 bpgs_50 bpgs_51 bpgs_52 bpgs_53 bpgs_54 bpgs_55 bpgs_56 bpgs_57 bpgs_58 bpgs_59 bpgs_60 bpgs_61 bpgs_62 bpgs_63 bpgs_64 bpgs_65 bpgs_66 bpgs_67 bpgs_68 Star HD 35296 BD +26 3780 HD 148816 HD 155675 PRAESEPE 418 HYAD 1 HD 122693 HD 154417 HYAD 2 HD 227547 HD 154760 HD 190605 HYAD 15 HD 139777A HD 136274 HYAD 26 HD 150205 HYAD 21 BD +02 3001 HD 190571 HYAD 183 HD 190470 HD 154712 HYAD 185 BD +38 2457 HYAD 173 GL 40 HYAD 189 HD 151288 HD 157881 HD 132683 GL 15A GL 49 GL 109 K7 V K7 V M0 V M0 V M2 V M4 V M0 V K8 V K3 V K4 V G8 V G8 V G5 V K0 V G8 V G5 V G2 V G2 V F8 V F8 V Type F8 V G0 V F9 V F8 V


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Appendix A: On-Line Catalogs and Spectral Atlases Table A.8: Bruzual-Persson-Gunn-Stryker Spectral Atlas File bpgs_69 bpgs_70 bpgs_71 bpgs_72 bpgs_73 bpgs_74 bpgs_75 bpgs_76 bpgs_77 bpgs_78 bpgs_79 bpgs_80 bpgs_81 bpgs_82 bpgs_83 bpgs_84 bpgs_85 bpgs_86 bpgs_87 bpgs_88 bpgs_89 bpgs_90 bpgs_91 bpgs_92 bpgs_93 bpgs_94 bpgs_95 bpgs_96 bpgs_97 bpgs_98 bpgs_99 bpgs_100 bpgs_101 bpgs_102 bpgs_103 Star GL 15B GL 83.1 GL 65 HR 7567 HR 7591 20 AQL HR 7467 IOTA LYR HR 7346 59 HER HR 6642 11 SGE 60 HER HD 192285 ALPHA OPH HD 165475B HD 165475 XI SER HD 5132 HD 508 HD 210875 RHO CAP HD 7331 BD +63 0013 HD 13391 HD 154962 HD 192344 HR 6516 HR 7670 HD 128428 31 AQL BD -02 4018 M67 F143? HD 11004 HD 173399A G5 IV G5 IV Type M6 V M8 V M5 V B1 IV B2 III B3 IV B3 III B7 IV B7 III A3 III A0 IV B9 IV A3 IV A4 IV A5 III A5 IV A5 IV F0 IV F0 IV A9 IV F0 IV F2 IV F7 IV F5 IV G2 IV G8 IV G4 IV G6 IV G6 IV G3 IV G8 IV G5 IV File bpgs_104 bpgs_105 bpgs_106 bpgs_107 bpgs_108 bpgs_109 bpgs_110 bpgs_111 bpgs_112 bpgs_113 bpgs_114 bpgs_115 bpgs_116 bpgs_117 bpgs_118 bpgs_119 bpgs_120 bpgs_121 bpgs_122 bpgs_123 bpgs_124 bpgs_125 bpgs_126 bpgs_127 bpgs_128 bpgs_129 bpgs_130 bpgs_131 bpgs_132 bpgs_133 bpgs_134 bpgs_135 bpgs_136 bpgs_137 bpgs_138 Star HD 56176 HD 227693 HD 199580 HD 152306 PRAESEPE 212 THETA1 TAU HD 170527 HD 136366 HD 191615 HD 124679 HD 131111 HD 113493 HD 4744 HD 7010 46 LMI 91 AQR M67 F141 HR 8924A HD 140301 HD 95272 HD 72184 HD 119425 HD 106760 PSI UMA PHI SER HD 136514 MU AQL HR 5227 HD 154759 20 CYG ALPH SER MU LEO BD +01 3131 M67 F170 18 LIB A K2 IIIp K3 III K0 IV K0 III K2 III K2 III K1 III K1 III K1 III K3 III K3 III K2 IIIp K3 III K3 III K2 III K2 III K0 III G8 III G5 IV K0 III G8 IV K0 III K0 III K0 III G8 IV K0 IV K0 III K0 III Type G7 IV G5 IV K2 IV G8 III


A.8: Jacoby-Hunter-Christian Spectophotometry Atlas Table A.8: Bruzual-Persson-Gunn-Stryker Spectral Atlas File bpgs_139 bpgs_140 bpgs_141 bpgs_142 bpgs_143 bpgs_144 bpgs_145 bpgs_146 bpgs_147 bpgs_148 bpgs_149 bpgs_150 bpgs_151 bpgs_152 bpgs_153 bpgs_154 bpgs_155 bpgs_156 bpgs_157 bpgs_158 bpgs_159 bpgs_160 Star BD +28 2165 NGC 188 1-69 BD +30 2344 HD 83618 HD 158885 HD 166780 HD 148513 M67 T626 HD 127227 M67 IV-202 HD 50778 HD 62721 HD 116870 HD 60522 BD -01 3113 BD +02 2884 BD -02 3873 HD 104216 HD 142804 HD 30959 HD 151658 BD -02 4025 K4 III K5 III M0 III M0 III K5 III K5 III M0 III M2 III M1 III M3 III M2 III M2 III K5 III K3 III K3 III K3 III K5 III K4 III Type K1 IV File bpgs_161 bpgs_162 bpgs_163 bpgs_164 bpgs_165 bpgs_166 bpgs_167 bpgs_168 bpgs_169 bpgs_170 bpgs_171 bpgs_172 bpgs_173 bpgs_174 bpgs_175 Star BD -01 3097 TX DRA Z CYG BD +01 3133 BD -02 3886 W HER TY DRA SW VIR RZ HER R LEO AW CYG WZ CAS 69 CYG HR 7699 HR 8020 N N

135

Type M2 III M8 III M5 III M5 III M6 III M8 M7 III M6 III

B0 Ib B5 Ib B8 Ia

A.8 Jacoby-Hunter-Christian Spectophotometry Atlas
This is an optical spectrophotometric atlas of 161 stars having spectral classes O through M and luminosity classes V, III, and I and are from the observations of Jacoby, Hunter, and Christian (1984). The spectra cover the wavelength range 3510 to 7427 å at a resolution of approximately 4.5 å. The spectra are available in STSDAS tables in the directory crgridjac$. The file names, star names, and spectral types for the JHC atlas are listed in Table A.9


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File
jc_1 jc_2 jc_3 jc_4 jc_5 jc_6 jc_7 jc_8 jc_9 jc_10 jc_11 jc_12 jc_13 jc_14 jc_15 jc_16 jc_17 jc_18 jc_19 jc_20 jc_21 jc_22 jc_23 jc_24 jc_25 jc_26 jc_27 jc_28 jc_29 jc_30 jc_31 jc_32 jc_33 jc_34

Star

Type

File
jc_35 jc_36 jc_37 jc_38 jc_39 jc_40 jc_41 jc_42 jc_43 jc_44 jc_45 jc_46 jc_47 jc_48 jc_49 jc_50 jc_51 jc_52 jc_53 jc_54 jc_55 jc_56 jc_57 jc_58 jc_59 jc_60 jc_61 jc_62 jc_63 jc_64 jc_65 jc_66 jc_67 jc_68

Star

Type

HD 242908 HD 215835 HD 12993 HD 35619 HD 44811 HD 242935 HD 236894 HD 17520 HD 12323 BD +62 0249 HD 158659 HD 237007 HD 35215 HD 37767 FEIGE 40 HD 240344 HD 30584 O 1015 HD 116608 FEIGE 41 HD 124320 FEIGE 28 HD 190785 HD 221741 HD 9547 HD 21619 HD 23863 HD 111525 HD 9972 HD 23733 HD 10032 Hz 948 HD 23511 Hz 227

O5 V O5.5 V O6.5 V O7 V O7.5 V O8 V O8 V O9 V O9 V O9.5 V B0 V B0 V B1.5 V B3 V B4 V B4 V B6 V B8 V A1 V A1 V A2 V A2 V A2 V A3 V A5 V A6 V A7 V A7 V A8 V A9 V F0 V F3 V F4 V F5 V

SAO 57199 HD 24189 HD 5702 HD 107132 HD 107214 HD 6111 HD 31084 HD 107399 HD 28099 HD 17647 HD 66171 BD +58 1199 Tr A14 HD 22193 HD 27685 HD 33278 HD 29050 HD 23524 HD 5351 SAO 76803 HD 260655 BD +63 0137 YALE 1755 HD 13505 HD 83140 HD 78277 HD 70178 HD 227018 SAO 11810 HD 191978 HD 16429 HD 13494 HD 12727 O 2311

F6 V F6 V F7 V F7 V F7 V F8 V F9 V F9 V G0 V G1 V G2 V G3 V G4 V G6 V G7 V G9 V G9 V K0 V K4 V K5 V M0 V M1 V M5 V F0 IV F3 IV G2 IV G5 IV O6.5 III O7.5 III O8.5 III O9.5 III B1 III B2 III B2 III


A.8: Jacoby-Hunter-Christian Spectophotometry Atlas Table A.9: Jacoby-Hunter-Christian Spectral Atlas (Continued)

137

File
jc_69 jc_70 jc_71 jc_72 jc_73 jc_74 jc_75 jc_76 jc_77 jc_78 jc_79 jc_80 jc_81 jc_82 jc_83 jc_84 jc_85 jc_86 jc_87 jc_88 jc_89 jc_90 jc_91 jc_92 jc_93 jc_94 jc_95 jc_96 jc_97 jc_98 jc_99 jc_100 jc_101 jc_102 jc_103

Star

Type

File
jc_104 jc_105 jc_106 jc_107 jc_108 jc_109 jc_110 jc_111 jc_112 jc_113 jc_114 jc_115 jc_116 jc_117 jc_118 jc_119 jc_120 jc_121 jc_122 jc_123 jc_124 jc_125 jc_126 jc_127 jc_128 jc_129 jc_130 jc_131 jc_132 jc_133 jc_134 jc_135 jc_136 jc_137 jc_138

Star

Type

SAO 11885 HD 166125 HD 39136 HD 56183 HD 256413 BD +61 0339 HD 28696 HD 20023 HD 12027 HD 240296 HD 12161 HD 64191 HD 5211 BD +61 0367 HD 56030 SAO 20603 HD 9979 HD 15866 BD +30 2347 HD 25894 HD 2506 BD +28 1885 HD 112872 HD 26514 HD 29883 HD 249240 HD 245389 SAO 55155 SAO 55164 HD 33506 SAO 77849 HD 26946 HD 21110 SAO 21753 SAO 63349

B2.5 III B3 III B4 III B4 III B5 III B7 III B8 III B9 III A3 III A6 III A8 III F0 III F4 III F5 III F6 III F7 III F8 III G0 III G0 III G2 III G4 III G5 III G6 III G6 III G6 III G7 III G8 III G9 III K0 III K2 III K2 III K3 III K4 III K7 III M3 III

HD 110964 SAO 62808 HD 14357 BD -14 4956 BD -00 3227 HD 249384 HD 250368 HD 249826 BD +19 1947 BD +36 1963 BD -11 4586 HD 225160 HD 16808 HD 167451 BD -14 5030 HD 209678 SAO 20899 HD 192832 BD +61 0220 HD 17145 LSI V P24 HD 209900 SAO 11344 SAO 12149 42 LSI SAO 87716 SAO 12096 HD 9167 HD 842 SAO 37370 BD +58 0204 HD 12842 SAO 21536 HD 9973 HD 8992

M4 III M5 III B2 II B2 II F5 II G8 II G9 II K6 II M3 II M7 II O8 I O8 I B0.5 Ib B0.5 Ib B1.5 Ia B2 Ib B3 I B5 Ia B7 I B8 Ia B9 Ib A0 Ib A0 Ib A1 I A2 I A3 Ia A4 I A7 I A9 I F0 Ib F2 I F3 I F4 I F5 Iab F6 Ib


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Appendix A: On-Line Catalogs and Spectral Atlases Table A.9: Jacoby-Hunter-Christian Spectral Atlas (Continued)

File
jc_139 jc_140 jc_141 jc_142 jc_143 jc_144 jc_145 jc_146 jc_147 jc_148 jc_149 jc_150

Star

Type

File
jc_151 jc_152 jc_153 jc_154 jc_155 jc_156 jc_157 jc_158 jc_159 jc_160 jc_161

Star

Type

HD 17971 HD 187428 HD 25361 SAO 21446 BD +56 0084 HD 191010 HD 187299 HD 186293 SAO 37325 HD 1069 HD 1400 HD 14330

F7 F8 G0 G1 G2 G3 G5 K0 K1 K2 K5 M1

I Ib Ia I I Ib I I Ib I I Iab

SAO 23888 HD 13136 HD 94028 SAO 102986 SAO 81292 HD 16691 HD 108 BD +40 4220 HD 13256 HD 50064 BD +51 0710

M1 I M2 Ib F4 V F7 V M4.5 Ve O5 If O6 If O7 If B1 Ia B1 Ia B5 Ib

A.9 Bruzual-Charlot Atlas
This is a library of galaxy spectra computed by Bruzual and Charlot using their Isochrone Synthesis Spectral Evolutionary Code. The December 1995 version of the Bruzual-Charlot atlas consists of 21 instantaneous bursts characterized by different IMF slope functions, and mass limits. Each instantaneous burst contains 221 spectral energy distributions (SEDs) corresponding to 221 time steps from 0 to 20 Gyr. The spectra represent bursts characterized by a Salpeter initial mass function (IMF) with different ranges in lower and upper mass limits, and at several ages (10E5, 25E5, 50E5, 76E5, 10E6, 25E6, 50E6, 10E7, 50E7, 10E8, 50E8, 10E9 years) after the burst. Spectra for instantaneous and composite bursts are available. Each spectrum has 1187 wavelength points covering the 100 Angstroms to 100 microns wavelength range, and the fluxes are given in units of solar luminosity per Angstrom. The nebular contribution to the spectral energy distribution, i.e., emission lines and nebular continuum, is not included in the spectra. The spectra have names of the form bc95_a_XXXX through bc95_g_XXXX and are located in the crgrid$bc95/templates/ directory.


A.10: Kinney-Calzetti Atlas

139

A.10 Kinney-Calzetti Atlas
This atlas consists of an homogeneous set of 12 spectral templates of galaxies covering the ultraviolet, optical and near-infrared wavelength range up to about 1 micron. Templates include various morphological types and starburst galaxies. The ultraviolet range of the spectral templates has been obtained with the large aperture (10" by 20") and low resolution spectrographs of the IUE satellite. The optical spectra were obtained through a long slit with a 10" width, where a window of 20" long was extracted to mach the IUE aperture. The spectral templates cover various galaxy morphological types from elliptical to late type spiral. Starburst templates for low (E(B-V) < 0.10) to high (0.61 < E(B-V) < 0.70) internal extinction are also available. Several of the starburst galaxies used in the construction of the starburst templates are classified as irregulars. Thus, although irregular galaxies are not explicitly covered, the starburst templates can be used to cover this morphological type. The flux of the spectral templates has been normalized to a visual magnitude of 12.5 (STMAG system). Details about each individual template can also be found in the header of the STSDAS binary file. The spectra are located in the crgrid$kc96/ directory.

A.11 Buser-Kurucz Atlas of Model Atmospheres
Roland Buser has provided an extensive collection of Kurucz model atmosphere spectra covering a wide range in metallicity, effective temperature, and gravity. They are organized into several atlases, A, B, C, D, M, and S, located in the directory crgridbk$. This atlas contains models computed by Kurucz in 1979. For a more complete and updated library of stellar atmosphere models, use the Kurucz 1993 atlas described above. The BK atlas is a library of stellar flux spectra calculated by Kurucz and Buser from theoretical model atmospheres. The spectra were computed for a wide range of physical parameters, covering essentially the whole HR diagram observed for galactic stars. For all the spectra, fluxes are given mostly with a resolution of 25 å on a uniform grid of wavelengths from the UV to the infrared. The BK atlas is thus especially suited for synthetic photometry applications (cf. Buser 1986, and references below), which


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also plays a major role in the calibration and the interpretation of HST observations (Koornneef et al. 1986). Therefore, the BK atlas has been implemented in the Calibration Data Base System (CDBS) at STScI. The BK atlas consists of 1434 files, each of which represents a metal-line blanketed flux spectrum for a theoretical stellar model atmosphere. There files were prepared from two original data libraries, K1200 and BKLATE. The K1200 library was computed by Kurucz (1979a,b) from his "ATLAS" model atmospheres for early-type (O to G) stars. The 1200 models were computed from three different versions of the "ATLAS" code, allowing for changes or improvements in the underlying physics, as shown in Table A.10: Table A.10: Kurucz K1200 Library
Models Code/Description Reference

K1200 1- 284 K1200 285- 609 K1200 610-1200

A

/ATLAS6 original

Kurucz 1979a Kurucz 1979b Kurucz 1979b

APR/ATLAS6 purely radiative AIC/ATLAS6 improved convective

K1200 models 1­284, including their flux spectra, have been fully published by Kurucz (1979a), while models 285­1200 were described by Kurucz (1979b), and have been widely distributed but not published. The BKLATE library was computed by Buser and Kurucz (1985, 1988, 1992) for late-type (F to K) stars from published as well as unpublished "GBEN" model atmospheres calculated by Gustafsson et al. (1975) and by Eriksson et al. (1979), respectively. Line-blanketed flux spectra were computed following the same procedure and employing the same opacity source input as in Kurucz (1979a). In particular, all the spectra were calculated using the extensive "KP" atomic line lists compiled by Kurucz and Peytremann (1975), and assuming a fixed turbulent velocity, vturb=2.00 km/s, and a fixed helium abundance, N(He)=0.10 (i.e., a number fraction of 10%). The BKLATE library data have not been published yet. For convenient use, the BK atlas flux spectra have been subdivided into separate blocks (or sub-atlases) corresponding to the physical distinctions of their underlying model atmospheres, as described above. Table A.11 summarizes the structure of the atlas.


A.11: Buser-Kurucz Atlas of Model Atmospheres Table A.11: BK Atlas

141

Block

Source of Spectra

# of Spectra

Models + Opacity

Teff

Log G

[M/H]

A B C D S

K1200 K1200 K1200 BKLATE K1200 BKLATE

279 323 590 233 3 1 5

A

+KP

5500­50000 8000­20000 5500­ 8500 3750­ 6000 5770,9400 5780 9400­10000

0.00­5.00 1.00­4.50 0.00­4.50 0.75­5.25 4.44,3.95 4.44 3.90­4.30

0/­1/­2 1/.5/­.5/­1 1 to ­9.99 .5 to ­3 0 0 0/.5/1

APR +KP AIC +KP GBEN +KP A/AIC+KP GBEN +KP A/APR+KP

M

K1200

Notice that within each of blocks A through D, models are available for ranges of usually uniformly spaced parameter values. Models are not available, however, for all possible combinations of parameter values. Block S contains models for two of the most prominent standard stars: three models of the Sun, and one model of Vega. Block M contains five miscellaneous models with special parameter combinations. The file names in the crgridbk$ directory are of the form bk_mnnnn.fits, where m is the block code (a, b, c, d, s, or m), and nnnn is a running sequence number within the block. Within each block, the individual models are ordered starting with the lowest metallicity, [M/H], temperature, Teff, and surface gravity, log G, and with log G increasing fastest and [M/H] increasing most slowly. A complete listing of all the BK atlas model spectra can be found in the README file in the crgridbk$ directory. For all 1434 models in the BK atlas, flux spectra are given for the same set of 342 wavelengths as was used with the published Kurucz (1979a) models. Most of these wavelength points cover the range between 229 å in the UV and about 2 microns in the IR, with spacings between 25 and 100 å. Fluxes in the BK atlas tables, tabulated in units of fnu, are surface fluxes. Therefore, calculations of absolute luminosities for the BK atlas models require additional assumptions about the radii of the stars represented by the models. A number of synthetic photometry applications have already been made using the BK atlas, mainly for the hotter Kurucz models from the K1200 library. A few pertinent references for theoretical calibrations of photometric systems are Lub and Pel (1977) for the Walraven VBLUW


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system, Buser and Kurucz (1978) for the Johnson UBV system, Relyea and Kurucz (1978) and Lester et al. (1986) for the Stromgren uvby system, and Buser and Kurucz (1988, 1992) for the Johnson-Cousins UBVRI system.

A.12 AGN Atlas
This atlas consists of a few spectral templates of AGNs ranging from LINER to Seyfert and bright QSO. The LINER and Seyfert 2 templates have been obtained with the large aperture (10" by 20") and low resolution spectrographs of the IUE satellite. The optical spectra were obtained through a long slit with a 10" width, where a window of 20" long was extracted to mach the IUE aperture (Calzetti 1995, private comm.). The flux of the LINER and Seyfert2 templates is normalized to a Johnson visual magnitude of 12.5 (STMAG). The Seyfert1 template consists of an UV spectrum obtained with the IUE low resolution spectrographs and of a ground-based optical spectrum. The bright QSO template is a composite spectrum from the Large Bright Quasar Survey of Francie and collaborators (1991). The Seyfert1 and QSO spectral templates are normalized to a Johnson blue magnitude of 12.5 (STMAG). The NGC 1068 template is a composite spectrum. The continuum contains the nebular, stellar, and power-law contributions. The observed fluxes and FWHM of the UV, optical and near-IR emission lines are also incorporated into the template (J.R. Walsh, private comm; read also the header of the FITS table for further details). The spectra are located in the crgrid$agn/ directory.

A.13 Galactic Atlas
This atlas consists of model spectra of the Orion Nebula and of the NGC 7009 planetary Nebula. The continuum of the Orion Nebula's template contains the nebular contribution plus a combination of Kurucz model atmospheres to simulate the stellar contribution. The fluxes of the UV, optical and near-IR emission lines from different sources are also incorporated into the template (J.R. Walsh, private comm.). The continuum of the planetery nebula has a nebular component and a hot stellar component simulated by an 80000K black body. The fluxes of the UV, optical and near-IR emission lines, from different sources, are also incorporated into the template (J.R. Walsh, private comm.). The spectra are located in the crgrid$galactic/ directory.


APPENDIX B:

Bibliography
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Colina, L., & Bohlin, R. 1997, AJ, 113, 1138 Colina, L., Bohlin, R.C., & Castelli, F. 1996, AJ, 112, 307 DeMarchi et al, 2004, ISR ACS 2004-08, "Detector Quantum Efficiency and Photometric Zero Points of the ACS" Eriksson, K., Bell, R.A., Gustafsson, B., Nordlund, A., 1979, Trans. IAU, Vol. 17A, Part 2, Reidel, Dordrecht, p. 200 Francis et al. 1991, ApJ 373, 465 . Greenfield, P. & White, R. L. 2000, in ASP Conf. Ser., Vol. 216, Astronomical Data Analysis Software and Systems IX, eds. N. Manset, C. Veillet, D. Crabtree (San Francisco: ASP), 59 Gunn, J.E. and Stryker, L.L., 1983, ApJS, 52, 121. Gustafsson, B., Bell, R.A., Eriksson, K., Nordlund, A., 1975, A&A, 42, 407. Harris, H., Baum, W., Hunter, D. and Kreidl, T., 1991, AJ, 101, 677. Heyer et al 2004, WFPC2 ISR 2004-01,"The Accuracy of WFPC2 Photometric Zeropoints" Hodge, P.E., 2004, "PyRAF Programmer's Guide" Horne, K., 1988, in New Directions in Spectrophotometry, A.G.D. Philip, D.S. Hayes, and S.J. Adelman, eds., L. Davis Press, Schenectady NY, p. 145. Horne, K., Burrows, C. and Koornneef, J., 1986, "Dynamic Generation of Throughput Functions: A Unified Approach," STScI Memo. Howarth, I.D., 1983, MNRAS, 203, 301. Jacoby, G.H., Hunter, D.A. and Christian, C.A., 1984, ApJS, 56, 257. Johnson, H.L., 1965, ApJ, 141, 923. Koornneef, J., Bohlin, R., Buser, R., Horne, K. and Turnshek, D., 1986, in Highlights of Astronomy, Vol. 7, J.-P. Swinds, ed., Reidel, Dordrecht, p. 833. Krist, J. & Hook, R. 2004 http://www.stsci.edu/software/tinytim (Ver. 6.3) Kurucz, R.L., 1979a, ApJS, 40, 1. Kurucz, R.L., 1979b, in Problems of Calibration of Multicolor Photometric Systems, Dudley Obs. Rep. No. 14, A.G. Davis Philip, ed., p. 363. Kurucz, R.L. and Peytremann, E., 1975, Smithsonian Astrophys. Obs. Rep. No. 362.


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Kurucz, R. 2003, http://kurucz.harvard.edu/ Landolt, A.U., 1983, AJ, 88, 439. Lester, J.B., Gray, R.O. and Kurucz, R.L., 1986, ApJS, 61, 509. Lub, J. and Pel, J.W., 1977, A&A, 54, 137. Matsushima, S., 1969, ApJ, 158, 1137. Oke, J.B., 1974, ApJS, 27, 21. Oke, J.B., and Gunn, J.E., 1983, ApJ, 266, 713. Oke, J.B. 1990, AJ, 99, 1621 Press, W.H., Teukolsky, S.A., Vetterling, W.T. and Flannery, B.P., 1992, Numerical Recipes in FORTRAN: The Art of Scientific Computing, Cambridge University Press, Cambridge. Relyea, L.L. and Kurucz, R.L., 1978, ApJS, 37, 45. Schneider, D.P., Gunn, J.E., and Hoessel, J.G., 1983, ApJ, 264, 337. Seaton, M.J., 1979, MNRAS, 187, 73p. Strecker, D.W., Erickson, E.F., and Whitteborn, F.C., 1979, ApJS, 41, 501. Turnshek, D.A., Bohlin, R.C., Williamson, R., Lupie, O., Koornneef, J., & Morgan D. 1990, AJ, 99, 1243 White and Greenfield, 1999, "The PyRAF Tutorial"


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Appendix B: Bibliography


Index
A ABMAG form parameter 22 accuracy 5 AGN atlas 142 B bandpar task 31 bandpass comparing 31 examining 31 bb function 20 blackbody function 20 Bruzual spectrum synthesis atlas 131 Bruzual-Charlot atlas 138 Bruzual-Persson-Gunn-Stryker spectrophotometry atlas 132 C calcband task 31, 34, 44 calcphot task 37, 46 calcspec task 50 cat function 20 combined throughput calculating 109 componenet table computation 109 component lookup table 6 component table default 27 component throughput table 6 countrate task 35, 37, 54 counts 22 estimating total 37 D data base synphot 4 directories location of catalogs and data 122 E ebmv 20 em 18 embvx 20 emission line function 18 emissivity table 113 examples cookbook 31 general syntax 15 photometry 37 spectra 34 expression evaluator syncalc 107 F fitband task 59 fitgrid task 68 fitspec task 63 fitting tasks to perform 14 flam 22 fnu 22 form parameter 15, 21 G galactic atlas 142
147


148

Index

galactic extinction 20 gauss 18 genwave task 72 grafcheck task 73 graflist task 74 Grafpath 75 graph table components in 74 computation 109 default 27 grid function 20 Gunn-Stryker spectrophotometry atlas 132 H help user support xii hi function 20 I icat function 20 imspec task 76 instrument graph table 6 error check 73 J Jacoby-Hunter-Christian atlas 135 jy 22 K keywords general discussion 3 Kinney-Calzetti atlas 139 Kurucz icat function 49 Kuruzc model atmospheres spectra using in synphot 139 L lgauss function 18 M mjy 22 spectrophotometry

Mkthru 78 Modeinfo 80 N NICMOS filter bandpass efficiency 33 O obmag 22 observation mode 15 observing mode specifying 3 obsmode parameter 15, 16 P parameter form 15, 21 refdata 15, 101 spectrum 15, 18 wavetable 15 passband creating 44 obsmode parameter 15 reconstruction, tasks to use 14 retrieving 3 photlam 22 photnu 22 photometric transformation plot creating 98 photometry examples 37 pl function 20 plband task 31, 82 plot spectra 34 plratio task 94 plspec task 34, 85 pltrans task 98 poly function 18 power law function 20 proposal utility of synphot 1 PyRAF 7


Index

149

R ratio observed to synthetic spectra 94 reddening ebmvx 20 redshift spectra, plotting 39 redshift function 20 refdata parameter 15, 27 refdata pset 101 reference data default values 27 refdata parameter 15 refdata pset 27 renormalize 20 rn function 20 S showfiles task 102 software obtaining xii spectra examples 34 photometric measurements 39 plotting 34 redshift 39 spectral atlases available in synphot 121 spectrum creating 50 spectrum parameter 15, 18 STIS CCD observation 35 stmag 22 syncalc expression evaluator 107 synphot capabilities 1 tasks in package 41 syntax commands and parameters 15 T tasks described 13, 41

passband reconstruction 14 telescope HST area 27 non-HST, using synphot with 6 thermal background 103 Thermback 103 throughput calculating combined 109 tilt function 18 U unit function 20 units specifying 21 specifying in form parameter 15 user support xii V variable substitution 26 VEGAMAG form parameter 22 VZERO 26 W wavelength set creating 72 wavelength table wavetab parameter 25 wavtable parameter 15 wavetab parameter 25 wavetable parameter 15 WFPC2 calcphot results 37 filter response 32 X XCAL relation to synphot 2 Z z function 20


150

Index