Comparative analysis of the NANOgrav Hellings-Downs as a window into new physics

TL;DR

This paper compares various models beyond standard cosmology to the Hellings-Downs correlation in pulsar timing array data, exploring their potential to reveal new physics through gravitational wave background signatures.

Contribution

It introduces a Bayesian framework to analyze four alternative models affecting the SGWB and assesses their statistical compatibility with observed data.

Findings

Spin-2 ultralight dark matter and massive gravity models are statistically similar to the Hellings-Downs prediction.

Weak evidence favors non-Gaussian components and ultralight vector dark matter.

Non-parametric tests indicate slight deviations from the Hellings-Downs curve, but data quality limits conclusions.

Abstract

Pulsar timing array (PTA) experiments have recently provided strong evidence for the signal of the stochastic gravitational wave background (SGWB) in the nHz-frequency band. These experiments have shown a statistical preference for the Hellings-Downs (HD) correlation between pulsars, which is widely regarded as a definitive signature of the SGWB. Using the NANOGrav 15-year dataset, we perform a comparative Bayesian analysis of four different models that go beyond the standard cosmological framework and influence the overlap reduction function. Specifically, we analyze ultralight vector dark matter (DM), spin-2 ultralight DM, massive gravity, and a folded non-Gaussian component to the SGWB. We find that the spin-2 ultralight DM and the massive gravity model are statistically equivalent to the HD prediction, and there is weak evidence in favor of the non-Gaussian component and the ultralight vector DM model. We also perform a non-parametric test using the Genetic Algorithms, which suggests a weak deviation from the HD curve. However, improved data quality is required before drawing definitive conclusions.