SI:CfA:HEA:ICHASC

AAS/HEAD 2013, Monterey, CA

131. Astrostatistics in High Energy Astrophysics

Special Session in memory of Alanna Connors

7:30pm-9:00pm, 8 Apr 2013, DeAnza Ballroom

This astrostatistics session will honor the memory of Alanna Connors. Alanna was a pioneer in the investigation and development of statistical methods required for the analysis of high energy data. The session will provide a historical perspective on Bayesian methods, highlight the topics where the contribution made by Alanna were particularly important, summarize current analysis challenges and discuss future perspectives.

Program

Chair: Herman Marshall (MIT)

 

Retrospective [20 min]

131.01 Alanna Connors and the Origins of Principled Data Analysis

Jeffrey D. Scargle (NASA/Ames)

Abstract: Alanna was one of the most important pioneers in the development of not just sophisticated algorithms for analyzing astronomical data but more importantly an overall viewpoint emphasizing the use of statistically sound principles in place of blind application of cook-book recipes, or black boxes. I will outline some of the threads of this viewpoint, emphasizing time series data, with a focus on the importance of these developments for the Age of Digital Astronomy that we are entering.

Presentation slides [.pdf]

 

Topics [5+2 min]

131.02 Promoting widespread use of Bayesian analysis

Keith Arnaud (NASA/GSFC)

Abstract: I will discuss incorporating Bayesian analysis in XSPEC and what is required for them to become the default option for high energy astrophysicists.

Presentation notes [.txt]

 

131.03 Hypothesis Tests

Aneta Siemiginowska (CfA)

Abstract: I will comment on statistical methods for hypothesis testing, highlighting the potential issues with using posterior predictive p-values or Bayes Factors.

Presentation slides [.pdf]

 

131.04 Using Bayesian Blocks to Trigger on Very High Energy Flares from Blazars

James Chiang (Stanford/SLAC)

Abstract: Owing to the continuous scanning observation mode of the Fermi satellite, the Large Area Telescope (LAT) is able to provide all-sky coverage on 3-hour time scales. However, this observing mode induces strong exposure modulations for any given location on the sky, making detection of transients on time scales of minutes to hours from objects problematic. I will discuss the application of the Bayesian Blocks algorithm to LAT data in a way that accounts for these exposure variations and show how the technique might be used to trigger on bright GeV-TeV-flaring blazars such as Mrk 421.

Presentation slides [.pdf]

 

131.05 A Statistical Approach to Recognizing Source Classes for Unassociated Sources in the Second Fermi-LAT Catalog

Maria Elena Monzani (Stanford/SLAC)

Abstract: We have developed a new and innovative technique to classify Fermi sources based solely on their observed gamma-ray properties. Our technique, based on Classification Trees, uses the properties of known objects to build a classification analysis which provides the probability for an unidentified source to belong to a given astronomical class (Pulsar, AGN,...). We have applied this technique to the second Fermi-LAT source catalog (2FGL), and computed a classification probability for each unidentified source. This provides a clearer picture of the unidentified source population and extends the number of interesting candidate objects, thus helping the community in scheduling multiwavelength observations.

Presentation slides [.pdf]

Extended illustration of analysis and methods are given in Ferrara et al. (2012 Fermi & Jansky Proceedings, arXiv/1206.2571)

 

131.06 LIRA: Low-counts Image Reconstruction and Analysis

Nathan M. Stein (Harvard)

Abstract: I will discuss LIRA, an R software package for multi-scale nonparametric image analysis in high energy astrophysics. LIRA uses Markov chain Monte Carlo to simultaneously fit an image and the necessary smoothing parameters, allowing for quantification of the standard error of the fitted image and evaluation of the goodness-of-fit of a proposed model.

Presentation slides [.pdf]

 

131.07 Systematic Errors

Vinay L. Kashyap (SAO)

Abstract: I will talk about methods to incorporate systematic errors into astrostatistical analysis, and discuss future prospects. In particular, I will point out how the pyBLoCXS algorithm lends itself to adding feedback, generalize to higher dimensions, and parameterize the sources of systematics.

Presentation slides [.pdf]

 

Prospective [20 min]

131.08 Possessing the field: Alanna Connors and the future of principled data analysis

Thomas J. Loredo (Cornell)

Abstract: Alanna emphasized the importance of adopting sound principles to guide statistical analysis of astronomical data. Her work and the work of her many collaborators and colleagues demonstrates the value of a principled approach. I will highlight two threads in her work: hierarchical Bayesian modeling, and nonparametric Bayesian modeling. I will note how these powerful ideas have influenced recent astrostatistics research, and point to how they might profitably merge for addressing the emerging problems of synoptic time-domain astronomy via Bayesian functional data analysis.

 

Posters and talks of interest

108.10. First Statistical Tests for Clumpy Torii Models: Constraints from RXTE Monitoring of Seyfert AGN

Alex Markowitz; Mirko Krumpe; Robert Nikutta

117.01. X-ray Reflected Spectra from Accretion Disk Models: A Complete Grid of Ionized Reflection Calculations

Javier Garcia; Thomas Dauser; Christopher S. Reynolds; Timothy R. Kallman; Jeffrey E. McClintock; Ramesh Narayan; Joern Wilms; Wiebke Eikmann

117.02. Two-temperature and Model-Independent Differential Emission Measure Distributions: The Emperor's New Clothes?

Kenneth G. Gayley

117.04. Statistical Methods in XSPEC

Keith A. Arnaud

117.05. The HEASARC in 2013 and Beyond: NuSTAR, Astro-H, NICER...

Stephen A. Drake; Alan P. Smale; Thomas A. McGlynn; Keith A. Arnaud

117.06. Application of an Improved Event Reconstruction and Imaging Approach for Compton Telescopes to Crab Measurements by NCT and COMPTEL Using MEGAlib

Andreas Zoglauer; Steven E. Boggs

117.07. Artificial Neural Networks as a Tool to Classify the 2FGL Unassociated Sources

David Salvetti

117.08. Earth Occultation Imaging of the Low Energy Gamma-ray Sky with GBM

James Rodi; Michael L. Cherry; Gary L. Case; Mark H. Finger; Peter Jenke; Colleen Wilson; Ascension Camero-Arranz; Vandiver Chaplin

117.09. Bayesian Methods in Sherpa

Aneta Siemiginowska; Thomas L. Aldcroft; Vinay Kashyap

126.16. Population Synthesis of Radio and Y­ray Normal, Isolated Pulsars Using Markov Chain Monte Carlo

Caleb Billman; Peter L. Gonthier; Alice K. Harding

127.23. Gamma-Ray Bursts: Pulses and Populations

Thomas J. Loredo; Jon E. Hakkila; Mary Beth Broadbent; Ira M. Wasserman; Robert L. Wolpert

204.03. A Statistical Approach to Identifying Compact Objects in X­ray Binaries

Saeqa D. Vrtilek

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