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Poisson vs. Gaussian statistics for sparse X-ray data: Application to the soft X-ray spectrometer
Tokyo Metropolitan Univ, Dept Phys, 1-1 Minami Osawa, Hachioji, Tokyo 1920397, Japan..
KTH, School of Engineering Sciences (SCI), Physics, Particle and Astroparticle Physics. Tokyo Metropolitan Univ, Dept Phys, 1-1 Minami Osawa, Hachioji, Tokyo 1920397, Japan..ORCID iD: 0000-0003-4378-8785
Tokyo Metropolitan Univ, Dept Phys, 1-1 Minami Osawa, Hachioji, Tokyo 1920397, Japan..
Tokyo Metropolitan Univ, Dept Phys, 1-1 Minami Osawa, Hachioji, Tokyo 1920397, Japan..
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2019 (English)In: Publications of the Astronomical Society of Japan, ISSN 0004-6264, E-ISSN 2053-051X, Vol. 71, no 4, article id 75Article in journal (Refereed) Published
Abstract [en]

Reliable results when fitting X-ray data require proper consideration of the statistics involved. We probe the impact of Gaussian versus Poisson statistics at low count levels using both the standard chi(2) method and maximum likelihood based on Poisson studied and quantified through simulated spectra with known properties. We then test the results through analysis of Mn K alpha calibration data taken with the flight spare microcalorimeter for the Hitomi soft X-ray spectrometer. Through comparison with simulations, our results show that the chi(2) method tends to give overly optimistic estimates of the detector energy resolution, in particular when there are few counts. Given an energy resolution of similar to 5eV and a line with about 100 photons, the line width becomes similar to 10% lower in the chi(2) method than in Poisson statistics. This is a consequence of the uncertainties being dominated by counting statistics, and therefore highlights the need to choose the appropriate fit statistic.

Place, publisher, year, edition, pages
OXFORD UNIV PRESS , 2019. Vol. 71, no 4, article id 75
Keywords [en]
instrumentation: detectors, methods: data analysis, methods: statistical
National Category
Astronomy, Astrophysics and Cosmology
Identifiers
URN: urn:nbn:se:kth:diva-259454DOI: 10.1093/pasj/psz053ISI: 000482425000009Scopus ID: 2-s2.0-85070811248OAI: oai:DiVA.org:kth-259454DiVA, id: diva2:1352973
Note

QC 20190920

Available from: 2019-09-20 Created: 2019-09-20 Last updated: 2019-09-20Bibliographically approved

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Axelsson, Magnus

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