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The NANOGrav 15 Yr Data Set: Removing Pulsars One by One from the Pulsar Timing Array

  • Gabriella Agazie
  • , Akash Anumarlapudi
  • , Anne M. Archibald
  • , Zaven Arzoumanian
  • , Jeremy G. Baier
  • , Paul T. Baker
  • , Bence Bécsy
  • , Laura Blecha
  • , Adam Brazier
  • , Paul R. Brook
  • , Sarah Burke-Spolaor
  • , J. Andrew Casey-Clyde
  • , 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, Heling Deng, Lankeswar Dey, Timothy Dolch, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Emiko C. Gardiner, Nate Garver-Daniels, Peter A. Gentile, Kyle A. Gersbach, 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, Bjorn Larsen, 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, Patrick M. Meyers, Hannah Middleton, Chiara M.F. Mingarelli, Andrea Mitridate, Christopher J. Moore, 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, Jessie C. Runnoe, Alexander Saffer, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Sophia V. Sosa Fiscella, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Stephen R. Taylor, Jacob E. Turner, Caner Unal, Michele Vallisneri, Alberto Vecchio, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, David Wright, Olivia Young
  • University of Wisconsin-Milwaukee
  • Newcastle University
  • NASA Goddard Space Flight Center
  • Oregon State University
  • Widener University
  • University of Florida
  • Cornell University
  • University of Birmingham
  • West Virginia University
  • University of Connecticut
  • Vanderbilt University
  • New Mexico Institute of Mining and Technology
  • Montana State University
  • Franklin and Marshall College, Lancaster
  • Naval Research Laboratory
  • University of British Columbia
  • George Mason University
  • National Science Foundation
  • Hillsdale College
  • Eureka Scientific, Inc.
  • University of Maryland, College Park
  • University of California at Berkeley
  • Haverford College
  • University of Michigan, Ann Arbor
  • California Institute of Technology
  • University of Washington
  • SETI Institute
  • Rochester Institute of Technology
  • Yale University
  • SUNY Oswego
  • University of Toronto
  • University of the Pacific
  • Union College
  • German Electron Synchrotron
  • University of Cambridge
  • Lafayette College
  • Carnegie Institution of Washington
  • Tufts University
  • Eötvös Loránd University
  • University of Puerto Rico
  • Texas Tech University
  • Pennsylvania State University
  • University of Münster
  • University of Colorado Boulder
  • Harvard & Smithsonian
  • Oberlin College
  • Max Planck Institute for Gravitational Physics (Albert Einstein Institute)
  • Middle East Technical University
  • Ben-Gurion University of the Negev
  • Bogazici University
  • Northwestern University
  • Adler Planetarium

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Evidence has emerged for a stochastic signal correlated among 67 pulsars within the 15 yr pulsar-timing data set compiled by the NANOGrav collaboration. Similar signals have been found in data from the European, Indian, Parkes, and Chinese pulsar timing arrays. This signal has been interpreted as indicative of the presence of a nanohertz stochastic gravitational-wave background (GWB). To explore the internal consistency of this result, we investigate how the recovered signal strength changes as we remove the pulsars one by one from the data set. We calculate the signal strength using the (noise-marginalized) optimal statistic, a frequentist metric designed to measure the correlated excess power in the residuals of the arrival times of the radio pulses. We identify several features emerging from this analysis that were initially unexpected. The significance of these features, however, can only be assessed by comparing the real data to synthetic data sets. After conducting identical analyses on simulated data sets, we do not find anything inconsistent with the presence of a stochastic GWB in the NANOGrav 15 yr data. The methodologies developed here can offer additional tools for application to future, more sensitive data sets. While this analysis provides an internal consistency check of the NANOGrav results, it does not eliminate the necessity for additional investigations that could identify potential systematics or uncover unmodeled physical phenomena in the data.

Original languageEnglish
Article number168
JournalAstrophysical Journal
Volume978
Issue number2
DOIs
StatePublished - Jan 1 2025

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