Gaussian process representation of dispersion measure noise in pulsar wideband datasets

TL;DR

This paper introduces a Gaussian process-based method to model and incorporate dispersion measure noise in wideband pulsar timing data, improving the robustness of pulsar timing array analyses.

Contribution

It generalizes existing methods by allowing arbitrary Gaussian process models of DM variation in pulsar timing and noise analysis.

Findings

Enables flexible modeling of DM noise with Gaussian processes

Improves robustness of pulsar timing in wideband datasets

Generalizes previous DM noise handling methods

Abstract

The ionized interstellar medium disperses pulsar radio signals, resulting in a stochastic time-variable delay known as the dispersion measure (DM) noise. In the wideband paradigm of pulsar timing, we measure a DM together with a time of arrival from a pulsar observation to handle frequency-dependent profile evolution, interstellar scintillation, and radio frequency interference more robustly, and to reduce data volumes. In this paper, we derive a method to incorporate arbitrary models of DM variation, including Gaussian process models, in pulsar timing and noise analysis and pulsar timing array analysis. This generalizes the existing method for handling DM noise in wideband datasets.