The NANOGrav 11-Year Data Set: Evolution of Gravitational Wave Background Statistics

TL;DR

This paper analyzes 11 years of NANOGrav pulsar data to improve detection methods for the gravitational wave background, addressing noise modeling and false positive mitigation.

Contribution

It introduces a new time slicing analysis and noise modeling techniques that enhance the reliability of gravitational wave background detection in pulsar timing data.

Findings

Effective noise modeling reduces false positives.

Identification of pulsars responsible for spurious signals.

Demonstrated robustness of gravitational wave statistics.

Abstract

An ensemble of inspiraling supermassive black hole binaries should produce a stochastic background of very low frequency gravitational waves. This stochastic background is predicted to be a power law, with a spectral index of -2/3, and it should be detectable by a network of precisely timed millisecond pulsars, widely distributed on the sky. This paper reports a new "time slicing" analysis of the 11-year data release from the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) using 34 millisecond pulsars. Methods to flag potential "false positive" signatures are developed, including techniques to identify responsible pulsars. Mitigation strategies are then presented. We demonstrate how an incorrect noise model can lead to spurious signals, and show how independently modeling noise across 30 Fourier components, spanning NANOGrav's frequency range, effectively diagnoses and absorbs the excess power in gravitational-wave searches. This results in a nominal, and expected, progression of our gravitational-wave statistics. Additionally we show that the first interstellar medium event in PSR J1713+0747 pollutes the common red noise process with low-spectral index noise, and use a tailored noise model to remove these effects.