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Bayesian Estimation of Hardness Ratios: Modeling and Computations

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Taeyoung Park1, Vinay L. Kashyap2, Aneta Siemiginowska2, David A. van Dyk3, Andreas Zezas2, Craig Heinke4 and Bradford J. Wargelin2

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A commonly used measure to summarize the nature of a photon spectrum is the so-called hardness ratio, which compares the numbers of counts observed in different passbands. The hardness ratio is especially useful to distinguish between and categorize weak sources as a proxy for detailed spectral fitting. However, in this regime classical methods of error propagation fail, and the estimates of spectral hardness become unreliable. Here we develop a rigorous statistical treatment of hardness ratios that properly deals with detected photons as independent Poisson random variables and correctly deals with the non-Gaussian nature of the error propagation. The method is Bayesian in nature and thus can be generalized to carry out a multitude of source-population-based analyses. We verify our method with simulation studies and compare it with the classical method. We apply this method to real-world examples, such as the identification of candidate quiescent low-mass X-ray binaries in globular clusters and tracking the time evolution of a flare on a low-mass star.


Subject headings

methods: statistical; stars: flare; X-rays: binaries


Dates

Issue 1 (2006 November 20)

Received 2005 December 24, accepted for publication 2006 June 14



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