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: http://www.adass.org/adass/proceedings/adass00/P1-26/
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The VIRMOS (Visible and Infrared Multi-Object Spectrograph) project
consists of two spectrographs with enhanced survey capabilities to be
installed on two unit telescopes of ESO Very Large Telescope (Chile):
VIMOS (0.37-1m) and NIRMOS (0.9-1.85
m), each one having
a large field of view (
) split into
four quadrants and a high
multiplexing factor (up to approximately 800 spectra per exposure).
To exploit such potential, a dedicated tool, the VIRMOS Mask Preparation Software (MPS), has been implemented. It provides the astronomer with tools for selecting objects to be observed spectroscopically, and for automatic slit positioning. The output of MPS is used to build the slit masks to be mounted in the instrument for the spectroscopic observations.
At a limiting
, the density of objects in the
sky is such that more than 1000 galaxies are visible in a VIMOS
quadrant. Of course, not all these objects can be observed
spectroscopically, as some requirements imposed by data quality have to be
taken into account when placing slits: the minimum slit length will
depend on the object size, since the slit must contain some area of
``pure sky'' to allow for a reliable sky subtraction; spectra must not
overlap either along the dispersion or the spatial direction; as each
first order spectrum is coupled with a second order spectrum which
will contaminate the first order spectrum of the slit above, a good
sky subtraction can be performed only if slits are aligned in columns
(same spatial coordinate) and, within the same column, have the same
length. All these factors lead to a theoretical maximum number of
spectra per quadrant of approximately 200.
Another requirement for MPS is set by the very good VLT seeing which
allows the use of slits widths of 0
3-0
4. Such narrow slits
imply an extremely precise slit positioning, with maximum
uncertainties of order 0
1. Thus the need for some (1-2
per quadrant) manually selected reference objects (possibly bright and
point-like) to be used for mask alignment. Moreover, the user must
have the possibility to choose manually some particularly interesting
sources to be included (Compulsory objects) and some others to be
excluded (Forbidden objects) from the spectroscopic sample. A
tool for manual definition of curved or tilted slits, to better follow
the shape of particularly interesting objects, must also be provided.
The MPS starts from a VIMOS image, to which a catalogue of objects is associated. The catalogue can be derived from the image itself or from some other astronomical dataset. In this second case, a way to correlate the celestial coordinates of the objects in the catalogue with image coordinates is to be provided. Some catalog handling capabilities, to allow for the selection of classes of sources among which to operate the choice of spectroscopic targets, some image display and catalogue overlay capabilities have to be provided by the package.
As MPS will be distributed to the astronomical community, it should be based on some already known package (Not Yet Another System). It was therefore decided to base the MPS GUI on the SKYCAT tool distributed by ESO. This tool allows astronomers to couple VIMOS images and catalogues on which to operate selections of objects over which to place slits.
A new panel for catalogue display and object selection (Reference, Compulsory, Forbidden object) has been implemented. For each type of catalogued object, a different overlay symbol has been defined.
A dedicated zoom panel allows the definition of curved/tilted slits. Curved slits are defined by fitting a Bezier curve to a set of points chosen by clicking on the zoom display. The fitted curve is then automatically plotted. The slit width is chosen through a scale widget.
Tilted slits can be defined as curved slits and then straightened. If the astronomer wants to have slits of a width different from the one chosen for the automatic slit placements, he can define them as tilted slits and then align them to the other automatically placed slits.
The core of Mask Preparation Software is the Slit Positioning Optimization Code (SPOC). Given a catalog of objects, SPOC maximizes the number of observable objects in a single exposure and computes the corresponding slit positions.
SPOC places slits on the field of view taking into account: special objects (reference, compulsory, forbidden), special slits (curved, tilted or user's dimension defined), spectral first order superposition, spectral higher order superposition and sky region parameter (the minimum amount of sky to be added to an object size when defining a slit).
The issue to be solved is a combinatorial computational problem.
Because of the constraint of slits aligned in the dispersion
direction, the problem can be simplified slightly: the quadrant area
can be considered as a sum of strips which are not necessarily of the
same width in the spatial direction. Slits within the same strip have
the same length and the alignment of orders is fully ensured. The
problem is thus reduced to be one dimension. It is easy to show
that the number of combination is roughly given by:
. The
slit length (or strip width) can vary from a minimum of 4arcsec (20
pixels, i.e., twice the minimum sky region required for the sky
subtraction) to a maximum of 30arcsec (150 pixels, limit imposed by
the slit laser cutting machine). The average number of strips can be
estimated as the spatial direction size of the FOV divided by the most
probable slit length: assuming the latter to be 50 pixels (10arcsec),
we would have
strips. The number of combinations would
then be:
.
Computing these many combinations would correspond to
years
of CPU work! The problem is similar to the well known traveling
salesman problem: in the standard approach, this is solved by randomly
extracting a ``reasonable'' number of combinations and maximizing over
this subsample. In our case, due to computational time, the
``reasonable'' number of combinations cannot be higher than
,
so small with respect to the total number of combination that the
result is not guaranteed to be near the real maximum. Our approach has
been to consider only the most ``probable'' combinations, i.e., the ones
that have the highest probability of maximizing the solution.
Step 1: For each spatial coordinate, we can vary the strip width from the given minimum to the given maximum, count how many objects we can place in the strip, and build the diagram of the number of slits in a strip divided by the strip width as a function of the strip width. For each spatial coordinate, only the strip widths corresponding to peaks in this histogram are worth considering, as they correspond to local maxima of the number of slits per strip. The exact positioning of the peaks varies for each spatial coordinate, but the shape of the function remains the same. The position of the peaks can be easily found in no more than 6-7 trials (using a partition exchange method).
Step 2: For each spatial coordinate we have K (where K is the number of peaks) possible strips, each with its own length and number of slits. Although the number of combinations to be tested is decreased, it is still too big in terms of computational time.
Step 3: A further reduction can be obtained if, instead of considering
all the strips simultaneously, we sequentially consider M subsets of N
consecutive strips, which together cover the whole FOV. At this point,
we should vary N (and consequently M) to find the best solution. In
practice, when N is higher than 8-10, nothing changes in terms of
number of observable objects. For N=10, thus M=4
(i.e.,
), the number of combinations is reduced to
only
-
, which means a few seconds of CPU
work. Unfortunately, as a consequence of the optimization process,
small size objects are favored against the big ones.
A second, less optimized algorithm has been implemented within SPOC.
This alternative algorithm does not optimize all strips simultaneously
but builds the
function strip by strip without
considering object sizes, and takes only the maximum of the
distribution. Then it enlarges each strip width by taking into account
object sizes. In this way the number of placed slits decreases by a
few percent but the object dimension bias disappears.
A dedicated panel for SPOC setup has been implemented within SKYCAT. Through this panel, users can select the grism, the slit width, the sky region parameter, the number of masks to be obtained for the given field, and the type of SPOC maximization.
The number of input slits and placed slits for all kinds of objects
(Reference, Compulsory, etc) is printed in a text box.
The slit catalogue produced by SPOC can be loaded as a normal SKYCAT catalog with overlay symbols defined for all kinds of objects, and it is also possible to plot the slit and spectrum overlay for all SPOC catalog objects.