TL;DR
The paper introduces the EXOD algorithm for detecting faint, fast X-ray transients in XMM-Newton data, leading to the discovery of four extragalactic neutron-star X-ray binaries and expanding the known neutron star population in M31.
Contribution
We developed a new variability detection algorithm, EXOD, capable of identifying faint, short-duration transients missed by standard methods in XMM-Newton data.
Findings
Detected 2,536 variable sources in 3XMM-DR8 catalog.
Discovered four extragalactic neutron-star X-ray binaries in M31.
Doubled the known neutron star population in M31.
Abstract
XMM-Newton has produced an extensive X-ray source catalogue in which the standard pipeline determines the variability of sufficiently bright sources through chi-square and fractional variability tests. Faint sources, however, are not automatically checked for variability, thus overlooking faint, short timescale transients. Our goal is to find new faint, fast transients in XMM-Newton EPIC-pn observations. To that end we have created the EPIC-pn XMM-Newton Outburst Detector (EXOD) algorithm, which we run on the EPIC-pn data available in the 3XMM-DR8 catalogue. In EXOD, we compute the whole-field variability by binning in time the counts in each detector pixel. We next compute the maximum-to-median count difference in each pixel to detect variability. We applied EXOD to 5,751 observations and compared the variability of the detected sources to the standard chi-square and Kolmogorov-Smirnov…
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