Measuring X-ray variability in faint/sparsely-sampled AGN
V. Allevato, M. Paolillo, I. Papadakis, C. Pinto

TL;DR
This paper investigates the biases in measuring X-ray variability in faint AGN using normalized excess variance, providing correction formulas and recommending ensemble estimates for more reliable results in current and future surveys.
Contribution
It introduces a bias correction formula for normalized excess variance and advocates for ensemble estimates to improve variability measurements in faint AGN.
Findings
Normalized excess variance is biased even with continuous sampling.
Bias depends on PSD slope and sampling pattern, not S/N ratio.
Ensemble estimates reduce uncertainty and improve variability measurement accuracy.
Abstract
We study the statistical properties of the Normalized Excess Variance of variability process characterized by a red-noise power spectral density (PSD), as the case of Active Galactic Nuclei (AGN). We perform Monte Carlo simulations of lightcurves, assuming both a continuous and a sparse sampling pattern and various signal-to-noise (S/N) ratios. We show that the normalized excess variance is a biased estimate of the variance even in the case of continuously sampled lightcurves. The bias depends on the PSD slope and on the sampling pattern, but not on the S/N ratio. We provide a simple formula to account for the bias, which yields unbiased estimates with an accuracy better than 15%. We show that the normalized excess variance estimates based on single lightcurves (especially for sparse sampling and S/N less than 3) are highly uncertain (even if corrected for bias) and we propose instead…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
