Mathematics – Probability
Scientific paper
Mar 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008head...10.4115l&link_type=abstract
American Astronomical Society, HEAD meeting #10, #41.15
Mathematics
Probability
Scientific paper
We have developed a fast, robust, and general method to incorporate effective area calibration uncertainties in model fitting of low-resolution spectra. Because such uncertainties are ignored during spectral fits, the error bars derived for model parameters are generally underestimated. Incorporating them directly into spectral analysis with existing analysis packages is not possible without extensive case-specific simulations, but it is possible to do so in a generalized manner in a Markov-Chain Monte Carlo framework. We describe our implementation of this method here, in the context of recently codified Chandra effective area uncertainties. We develop our method and apply it to both simulated as well as actual Chandra ACIS-S data. We estimate the posterior probability densities of power-law model parameters that include the effects of such uncertainties. We describe a file format based on the HEASARC ARF standard which will allow these uncertainties to be included during analysis in any astronomical spectral fitting package.
This research was supported by NASA/AISRP grant NNG06GF17G and NASA contract NAS8-39073 to the Chandra X-Ray Center.
Connors Alanna
Drake Jeremy J.
Izem Rima
Kashyap Vinay
Lee Hyunsook
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