Modeling non stationary noise in pulsar timing array data analysis

TL;DR

This paper introduces a non-stationary Gaussian process model to analyze pulsar timing array data, investigates the evolution of the gravitational wave background over time, and finds no significant non-stationary behavior.

Contribution

The paper presents a novel approximated non-stationary Gaussian process model for PTA data analysis and applies it to real data to search for non-stationary features in the GWB.

Findings

No evidence for non-stationary behavior in the GWB.

GWB properties evolve with observation improvements.

Non-stationarity may arise from noise or eccentric sources.

Abstract

Pulsar Timing Array (PTA) collaborations recently reported evidence for the presence of a gravitational wave background (GWB) in their datasets. The main candidate that is expected to produce such a GWB is the population of supermassive black hole binaries (SMBHB). Some analyses showed that the recovered signal may exhibit time-dependent properties, i.e. non-stationarity. In this paper, we propose an approximated non-stationary Gaussian process (GP) model obtained from the perturbation of stationary processes. The presented method is applied to the second data release of the European pulsar timing array to search for non-stationary features in the GWB. We analyzed the data in different time slices and showed that the inferred properties of the GWB evolve with time. We find no evidence for such non-stationary behavior and the Bayes factor in favor of the latter is $\mathcal{B}^{NS}_{S} = 1.5$. We argue that the evolution of the GWB properties most likely comes from the \mf{improvement of the observation cadence} with time and \mf{better} characterization of the noise of individual pulsars. Such non-stationary GWB could also be produced by the leakage of non-stationary features in the noise of individual pulsars or by the presence of an eccentric single source.