The Astrophysical Journal Letters (Jan 2023)

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

  • Gabriella Agazie,
  • Akash Anumarlapudi,
  • Anne M. Archibald,
  • Zaven Arzoumanian,
  • Paul T. Baker,
  • Bence Bécsy,
  • Laura Blecha,
  • Adam Brazier,
  • Paul R. Brook,
  • Sarah Burke-Spolaor,
  • Maria Charisi,
  • Shami Chatterjee,
  • Tyler Cohen,
  • James M. Cordes,
  • Neil J. Cornish,
  • Fronefield Crawford,
  • H. Thankful Cromartie,
  • Kathryn Crowter,
  • Megan E. DeCesar,
  • Paul B. Demorest,
  • Timothy Dolch,
  • Brendan Drachler,
  • Elizabeth C. Ferrara,
  • William Fiore,
  • Emmanuel Fonseca,
  • Gabriel E. Freedman,
  • Nate Garver-Daniels,
  • Peter A. Gentile,
  • Joseph Glaser,
  • Deborah C. Good,
  • Lydia Guertin,
  • Kayhan Gültekin,
  • Jeffrey S. Hazboun,
  • Ross J. Jennings,
  • Aaron D. Johnson,
  • Megan L. Jones,
  • Andrew R. Kaiser,
  • David L. Kaplan,
  • Luke Zoltan Kelley,
  • Matthew Kerr,
  • Joey S. Key,
  • Nima Laal,
  • Michael T. Lam,
  • William G. Lamb,
  • T. Joseph W. Lazio,
  • Natalia Lewandowska,
  • Tingting Liu,
  • Duncan R. Lorimer,
  • Jing Luo,
  • Ryan S. Lynch,
  • Chung-Pei Ma,
  • Dustin R. Madison,
  • Alexander McEwen,
  • James W. McKee,
  • Maura A. McLaughlin,
  • Natasha McMann,
  • Bradley W. Meyers,
  • Chiara M. F. Mingarelli,
  • Andrea Mitridate,
  • Cherry Ng,
  • David J. Nice,
  • Stella Koch Ocker,
  • Ken D. Olum,
  • Timothy T. Pennucci,
  • Benetge B. P. Perera,
  • Nihan S. Pol,
  • Henri A. Radovan,
  • Scott M. Ransom,
  • Paul S. Ray,
  • Joseph D. Romano,
  • Shashwat C. Sardesai,
  • Ann Schmiedekamp,
  • Carl Schmiedekamp,
  • Kai Schmitz,
  • Brent J. Shapiro-Albert,
  • Xavier Siemens,
  • Joseph Simon,
  • Magdalena S. Siwek,
  • Ingrid H. Stairs,
  • Daniel R. Stinebring,
  • Kevin Stovall,
  • Abhimanyu Susobhanan,
  • Joseph K. Swiggum,
  • Stephen R. Taylor,
  • Jacob E. Turner,
  • Caner Unal,
  • Michele Vallisneri,
  • Sarah J. Vigeland,
  • Haley M. Wahl,
  • Caitlin A. Witt,
  • Olivia Young,
  • The NANOGrav Collaboration

DOI
https://doi.org/10.3847/2041-8213/acda88
Journal volume & issue
Vol. 951, no. 1
p. L10

Abstract

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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.

Keywords