Hidden biases in flux-resolved X-ray spectroscopy

TL;DR

This paper identifies two hidden biases in flux-resolved X-ray spectroscopy caused by Poisson fluctuations, which can distort spectral analysis results, especially in background estimation and flux level determination.

Contribution

It reveals previously overlooked biases in flux-resolved X-ray spectroscopy and proposes methods to assess and correct these biases for more accurate spectral analysis.

Findings

Poisson fluctuations can bias flux level estimation.

Background count fluctuations affect spectral parameter accuracy.

Bias correction methods improve spectral analysis reliability.

Abstract

Flux-resolved X-ray spectroscopy is widely adopted to investigate the spectral variation of a target between various flux levels. In many cases it is done through horizontally splitting a single light curve into multiple flux levels with certain count rate threshold(s). In this work we point out there are two hidden biases in this approach which could affect the spectral analyses under particular circumstances. The first is that, when Poisson fluctuations of the source counts in light curve bins are non-negligible compared with the intrinsic variation, this approach would over-estimate (under-estimate) the intrinsic average flux level of the high (low) state. The second bias is that, when the Poisson fluctuations of the background count rate is non-negligible, the background spectrum of the high (low) state would be under-estimated (over-estimated), thus yielding biased spectral fitting parameters. We take NuSTAR spectra for example to illustrate the effects of the biases, and particularly, how the measurements of the coronal temperature in AGNs would be biased. We present a toy method to assess the significance of such biases, and approaches to correct for them when necessary.