Characterizing the nanohertz gravitational wave background using a $t$-process power spectral density

TL;DR

This paper introduces a $t$-process power spectral density model for pulsar timing array data to better characterize the nanohertz gravitational wave background, capturing deviations from the standard power-law due to individual sources.

Contribution

The paper proposes using a $t$-process PSD to model the GWB, enabling detection of deviations from a power-law caused by discrete SMBHB sources.

Findings

$t$-process PSD accurately recovers the spectrum with deviations.

Simulated data shows improved modeling of complex GWB spectra.

Method enhances the ability to distinguish individual sources.

Abstract

Pulsar timing arrays are sensitive to low-frequency gravitational waves (GWs), which induce correlated changes in millisecond pulsars' timing residuals. PTA collaborations around the world have recently announced evidence of a nanohertz gravitational wave background (GWB), which may be produced by a population of supermassive black hole binaries (SMBHBs). The GWB is often modeled as following a power-law power spectral density (PSD); however, a GWB produced by a cosmological population of SMBHBs is expected to have a more complex power spectrum due to the discrete nature of the sources. In this paper, we investigate using a $t$-process PSD to model the GWB, which allows us to fit for both the underlying power-law amplitude and spectral index as well as deviations from that power law, which may be produced by individual nearby binaries. We create simulated data sets based on the properties of the NANOGrav 15-year data set, and we demonstrate that the $t$-process PSD can accurately recover the PSD when deviations from a power-law are present. With longer timed datasets and more pulsars, we expect the sensitivity of our PTAs to improve, which will allow us to precisely measure the PSD of the GWB and study the sources producing it.