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American Astronomical Society, Astrophysical Journal Letters, 1(951), p. L10, 2023

DOI: 10.3847/2041-8213/acda88

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The NANOGrav 15 yr Data Set: Detector Characterization and Noise Budget

Journal article published in 2023 by Gabriella Agazie ORCID, T. Joseph W. Lazio, Akash Anumarlapudi ORCID, Anne M. Archibald ORCID, Zaven Arzoumanian, Paul T. Baker ORCID, Bence Bécsy ORCID, Laura Blecha ORCID, Adam Brazier ORCID, Paul R. Brook ORCID, Sarah Burke-Spolaor ORCID, Maria Charisi ORCID, Shami Chatterjee ORCID, Tyler Cohen ORCID, James M. Cordes ORCID and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Pulsar timing arrays (PTAs) are galactic-scale gravitational wave (GW) detectors. Each individual arm, composed of a millisecond pulsar, a radio telescope, and a kiloparsecs-long path, differs in its properties but, in aggregate, can be used to extract low-frequency GW signals. We present a noise and sensitivity analysis to accompany the NANOGrav 15 yr data release and associated papers, along with an in-depth introduction to PTA noise models. As a first step in our analysis, we characterize each individual pulsar data set with three types of white-noise parameters and two red-noise parameters. These parameters, along with the timing model and, particularly, a piecewise-constant model for the time-variable dispersion measure, determine the sensitivity curve over the low-frequency GW band we are searching. We tabulate information for all of the pulsars in this data release and present some representative sensitivity curves. We then combine the individual pulsar sensitivities using a signal-to-noise ratio statistic to calculate the global sensitivity of the PTA to a stochastic background of GWs, obtaining a minimum noise characteristic strain of 7 × 10−15 at 5 nHz. A power-law-integrated analysis shows rough agreement with the amplitudes recovered in NANOGrav’s 15 yr GW background analysis. While our phenomenological noise model does not model all known physical effects explicitly, it provides an accurate characterization of the noise in the data while preserving sensitivity to multiple classes of GW signals.