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arXiv · 2111.04244

Selection Effects in Periodic X-ray Data from Maximizing Detection Statistics

Abstract

The Neutron Star Interior Composition Explorer (NICER) records data of exceptional quality on the energy-dependent X-ray pulse profile of pulsars. However, in searching for evidence of pulsations, Guillot et al. (2019) introduce a procedure to select an ordered subset of the data that maximizes a detection statistic (the H-test). I show that this procedure can degrade subsequent analyses using an idealized model with a stationary expected count rates from both noise and signal. Specifically, the data-selection procedure biases the inferred mean count rate to be too low, biases the inferred pulsation amplitude to be too high, and that the size of these biases scales strongly with the amount of data that is rejected and the true signal amplitude. The procedure also alters the null-distribution of the H-test rendering nominal detection significance estimates overly optimistic. While the idealized model does not capture all the complexities of real NICER data, it suggests that these biases could be important for NICER's observations of J0740+6620 and other faint pulsars (observations of J0030+0451 are likely less affected). I estimate that these selection effects may introduce a bias of $\mathcal{O}(10\%)$ on average in the inferred modulation depth of lightcurves like J0740+6620's, and may be as large as $\mathcal{O}(50\%)$ for fainter pulsars. However, the change for a single dataset like J0740+6620 is expected to be a shift between $-5\%$ and $+20\%$. This could imply that the lower limit on J0740+6620's radius is slightly larger than it should be, although preliminary investigations suggest the change in the radius constraints are $\mathcal{O}(1\%)$ with real J0740+6620 data.

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BibTeXRIS

Reed Essick. 2021-11-08. Selection Effects in Periodic X-ray Data from Maximizing Detection Statistics. https://doi.org/10.3847/1538-4357%2Fac517c

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