Time domain methods for X-ray and gamma-ray astronomy
Abstract
A variety of statistical methods for understanding variability in the time domain for low count rate X-ray and gamma-ray sources are explored. Variability can be detected using nonparametric (Anderson-Darling and overdispersion tests) and parametric (sequential likelihood-based tests) tools. Once detected, variability can be characterized by nonparametric (autocorrelation function, structure function,wavelet analysis) and parametric (multiple change point model such as Bayesian Blocks, integer autoregressive models, C-statistic and Poisson regression) methods. New multidimensional variability detection approaches are outlined. Software packages designed for high energy data analysis are deficient but tools are available in the R statistical software environment. Most of the methods presented here are not commonly used in high energy astronomy.
Cite
@article{arxiv.2203.08996,
title = {Time domain methods for X-ray and gamma-ray astronomy},
author = {Eric D. Feigelson and Vinay L. Kashyap and Aneta Siemiginowska},
journal= {arXiv preprint arXiv:2203.08996},
year = {2023}
}
Comments
26 pages, 9 figures. To appear in Handbook for X-ray and Gamma-Ray Astrophysics, Volume 4: Analysis techniques, Section XVIII: Timing Analysis (Belloni & Bhattacharya, eds., Springer)