Photon-Count Statistics of Crab X-ray Pulses: Skellam Behavior and Excess Variance in the Main Pulse

TL;DR

This study analyzes Crab pulsar X-ray pulses using NICER data, demonstrating Skellam distribution behavior in photon counts and identifying excess variance in the main pulse, with implications for pulsar emission models.

Contribution

It provides the first high-statistics empirical demonstration of Skellam behavior in astrophysical photon-count data and explores pulse variability and correlations.

Findings

IP photon counts follow Skellam distribution

Main pulse shows excess variance driven by high counts

No significant lag-1 correlation between pulses

Abstract

The Crab pulsar (PSR B0531+21) provides an unusually rich test bed for statistical studies of high-energy photon-counting data, owing to its extreme brightness and the contrasting behavior of its main pulse (MP) and interpulse (IP) components. Using 78.8 ks of Neutron star Interior Composition Explorer (NICER; Gendreau and Arzoumanian 2017) data-over two million individual X-ray pulses- we construct the single-pulse photon-count distributions of the MP and IP at keV energies. We find that the IP is well described by the Skellam distribution expected for the difference of two Poisson processes, providing a rare, high-statistics empirical demonstration of Skellam behavior in an astrophysical photon-counting context. The MP also shows pulse-by-pulse variability best described by a Skellam framework when compared to Gaussian alternatives, but exhibits a significant excess variance driven by high-count events. When photon counts are summed over successive pulses, this excess averages out and the MP distribution becomes consistent with Skellam expectations, indicating that the enhanced variability does not persist across rotations. We further search for short-lag (memory) correlations between successive X-ray pulses and find no statistically significant lag-1 correlation. Although giant radio pulses occur in the MP phase window, their contribution is insufficient to account for the observed excess variability. Together, these results highlight a clear statistical distinction between the MP and IP and underscore the importance of using statistically appropriate models for high-energy photon-counting analyses. The distributional fits and memory limits reported here provide quantitative constraints on pulsar emission models and illustrate the broader utility of Skellam-based approaches.