Paper
12 July 2008 How to handle calibration uncertainties in high-energy astrophysics
Vinay L. Kashyap, Hyunsook Lee, Aneta Siemiginowska, Jonathan McDowell, Arnold Rots, Jeremy Drake, Pete Ratzlaff, Andreas Zezas, Rima Izem, Alanna Connors, David van Dyk, Taeyoung Park
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Abstract
Unlike statistical errors, whose importance has been well established in astronomical applications, uncertainties in instrument calibration are generally ignored. Despite wide recognition that uncertainties in calibration can cause large systematic errors, robust and principled methods to account for them have not been developed, and consequently there is no mechanism by which they can be incorporated into standard astronomical data analysis. Here we present a framework where they can be encoded such that they can be brought within the scope of analysis. We describe this framework, which is based on a modified MCMC algorithm, and propose a format standard derived from experience with effective area measurements of the ACIS-S detector on Chandra that can be applied to any instrument or method of codifying systematic errors. Calibration uncertainties can then be propagated into model parameter estimates to produce error bars that include systematic error information.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vinay L. Kashyap, Hyunsook Lee, Aneta Siemiginowska, Jonathan McDowell, Arnold Rots, Jeremy Drake, Pete Ratzlaff, Andreas Zezas, Rima Izem, Alanna Connors, David van Dyk, and Taeyoung Park "How to handle calibration uncertainties in high-energy astrophysics", Proc. SPIE 7016, Observatory Operations: Strategies, Processes, and Systems II, 70160P (12 July 2008); https://doi.org/10.1117/12.788372
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Calibration

Error analysis

Monte Carlo methods

Principal component analysis

Data modeling

Sensors

Statistical analysis

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