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The NANOGrav 11 yr Data Set: Evolution of Gravitational-wave Background Statistics

  • M. Vallisneri
  • , J. S. Hazboun
  • , J. Simon
  • , S. R. Taylor
  • , M. T. Lam
  • , S. J. Vigeland
  • , K. Islo
  • , J. S. Key
  • , Z. Arzoumanian
  • , P. T. Baker
  • , A. Brazier
  • , P. R. Brook
  • , S. Burke-Spolaor
  • , S. Chatterjee
  • , J. M. Cordes
  • , N. J. Cornish
  • , F. Crawford
  • , K. Crowter
  • , H. T. Cromartie
  • , M. Decesar
  • P. B. Demorest, T. Dolch, J. A. Ellis, R. D. Ferdman, E. Ferrara, E. Fonseca, N. Garver-Daniels, P. Gentile, D. Good, A. M. Holgado, E. A. Huerta, R. Jennings, G. Jones, M. L. Jones, A. R. Kaiser, D. L. Kaplan, L. Z. Kelley, T. J.W. Lazio, L. Levin, A. N. Lommen, D. R. Lorimer, J. Luo, R. S. Lynch, D. R. Madison, M. A. McLaughlin, S. T. McWilliams, C. M.F. Mingarelli, C. Ng, D. J. Nice, T. T. Pennucci, N. S. Pol, S. M. Ransom, P. S. Ray, X. Siemens, R. Spiewak, I. H. Stairs, D. R. Stinebring, K. Stovall, J. Swiggum, J. E. Turner, M. Vallisneri, R. Van Haasteren, C. A. Witt, W. W. Zhu
  • California Institute of Technology
  • University of Washington
  • Jet Propulsion Laboratory, California Institute of Technology
  • Vanderbilt University
  • Rochester Institute of Technology
  • West Virginia University
  • University of Wisconsin-Milwaukee
  • NASA Goddard Space Flight Center
  • Widener University
  • Cornell University
  • Montana State University
  • Franklin and Marshall College, Lancaster
  • University of British Columbia
  • University of Virginia
  • Lafayette College
  • National Science Foundation
  • Hillsdale College
  • University of East Anglia
  • McGill University
  • University of Illinois at Urbana-Champaign
  • Columbia University
  • Northwestern University
  • University of Manchester
  • Haverford College
  • University of Texas at San Antonio
  • University of Texas Rio Grande Valley
  • Simons Foundation
  • University of Toronto
  • Eötvös Loránd University
  • Naval Research Laboratory
  • Swinburne University of Technology
  • Oberlin College
  • Chinese Academy of Sciences

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

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 gravitational-wave strain 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 yr 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 we 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 we use a tailored noise model to remove these effects.

Original languageEnglish
Article number108
JournalAstrophysical Journal
Volume890
Issue number2
DOIs
StatePublished - Feb 20 2020

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