The NANOGrav 15 yr dataset: Posterior predictive checks for gravitational-wave detection with pulsar timing arrays

Pulsar timing array experiments have reported evidence for a stochastic background of nanohertz gravitational waves consistent with the signal expected from a population of supermassive black hole binaries. Their analyses assume power-law spectra for intrinsic pulsar noise and for the background, as well as a Hellings-Downs cross-correlation pattern among the gravitational-wave-induced residuals across pulsars. These assumptions may not be realized in actuality. We test them in the NANOGrav 15 yr dataset using Bayesian posterior predictive checks. After fitting our fiducial model to real data, we generate a population of simulated dataset replications. We use the replications to assess whether the optimal statistic significance, interpulsar correlations, and spectral coefficients are extreme. We recover Hellings-Downs correlations in simulated datasets at significance levels consistent with the correlations measured in the NANOGrav 15 yr dataset. A similar test on spectral coefficients shows that their values in real data are not extreme compared to their distributions across replications. We also evaluate the evidence for the stochastic background using posterior predictive versions of the frequentist optimal statistic and of Bayesian model comparison and find comparable significance ($3.2\ensuremath{\sigma}$ and $3\ensuremath{\sigma}$ respectively) to what was previously reported for the standard statistics. We conclude with novel visualizations of the reconstructed gravitational waveforms that enter the residuals for each pulsar. Our analysis strengthens confidence in the identification and characterization of the gravitational-wave background.

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Publication Details

Journal
Physical review. D/Physical review. D.
Published
2025-02-28
DOI
https://doi.org/10.1103/physrevd.111.042011
Citations
3
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
3.46

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The NANOGrav 15 yr dataset: Posterior predictive checks for gravitational-wave detection with pulsar timing arrays

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3 citations
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Pulsars and Gravitational Waves Research
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article

The NANOGrav 15 yr dataset: Posterior predictive checks for gravitational-wave detection with pulsar timing arrays

Aaron D. Johnson, Dustin R. Madison, Bjorn Larsen, Sarah J. Vigeland, Caner Ünal, J. M. Cordes, Neil J. Cornish, H. Thankful Cromartie, Natasha McMann, Laura Blecha, J. S. Key, Ken D. Olum, Bradley W. Meyers, Alexander McEwen, James W. McKee, M. A. McLaughlin, J. Andrew Casey-Clyde, Carl Schmiedekamp, B. Bécsy, Nihan S. Pol, Timothy Dolch, Nima Laal, E. C. Ferrara, S. M. Ransom, Akash Anumarlapudi, Luke Zoltan Kelley, J. G. Baier, Emiko C. Gardiner, David J. Nice, Sarah Burke-Spolaor, T. Joseph, David L. Kaplan, Anne M. Archibald, William Fiore, Caitlin A. Witt, Tyler Cohen, Gabriel E. Freedman, Michael T. Lam, Deborah C. Good, Olivia Young, Michele Vallisneri, W. Lazio, Haley M. Wahl, Kayhan Gültekin, Abhimanyu Susobhanan, Joseph Glaser, Lankeswar Dey, Nate Garver-Daniels, Peter A. Gentile, Ryan S. Lynch, Shashwat C. Sardesai, Ingrid H. Stairs, Brent J. Shapiro-Albert, Kathryn Crowter, Timothy T. Pennucci, Duncan R. Lorimer, P. T. Baker, Paul R. Brook, Ross J. Jennings, Kai Schmitz, Maria Charisi, Alexander Saffer, Shami Chatterjee, Chiara M. F. Mingarelli, Adam Brazier, David Wright, Andrea Mitridate, Ann Schmiedekamp, Paul B. Demorest, Jeffrey S. Hazboun, Heling Deng, Kevin Stovall, Matthew T. Kerr, Jessie C. Runnoe, F. Crawford, Daniel R. Stinebring, Paul S. Ray, Magdalena S. Siwek, Benetge B. P. Perera, Megan L. Jones, N. Lewandowska, Joseph Simon, William G. Lamb, Zaven Arzoumanian, Andrew R. Kaiser, Jing Luo, P. M. Meyers, Jacob E. Turner, Stella Koch Ocker, Cherry Ng, Chung‐Pei Ma, Gabriella Agazie, Megan E. DeCesar, Joseph K. Swiggum, Tingting Liu, Emmanuel Fonseca, Kyle A. Gersbach, H. A. Radovan, Sophia V. Sosa Fiscella, Stephen R. Taylor, Katerina Chatziioannou, Joseph D. Romano, X. Siemens
article en
3 citations

Abstract

Pulsar timing array experiments have reported evidence for a stochastic background of nanohertz gravitational waves consistent with the signal expected from a population of supermassive black hole binaries. Their analyses assume power-law spectra for intrinsic pulsar noise and for the background, as well as a Hellings-Downs cross-correlation pattern among the gravitational-wave-induced residuals across pulsars. These assumptions may not be realized in actuality. We test them in the NANOGrav 15 yr dataset using Bayesian posterior predictive checks. After fitting our fiducial model to real data, we generate a population of simulated dataset replications. We use the replications to assess whether the optimal statistic significance, interpulsar correlations, and spectral coefficients are extreme. We recover Hellings-Downs correlations in simulated datasets at significance levels consistent with the correlations measured in the NANOGrav 15 yr dataset. A similar test on spectral coefficients shows that their values in real data are not extreme compared to their distributions across replications. We also evaluate the evidence for the stochastic background using posterior predictive versions of the frequentist optimal statistic and of Bayesian model comparison and find comparable significance ($3.2\ensuremath{\sigma}$ and $3\ensuremath{\sigma}$ respectively) to what was previously reported for the standard statistics. We conclude with novel visualizations of the reconstructed gravitational waveforms that enter the residuals for each pulsar. Our analysis strengthens confidence in the identification and characterization of the gravitational-wave background.

Physical review. D/Physical review. D.Vol. 111(4)
National Science Foundation, National Aeronautics and Space Administration, Alfred P. Sloan Foundation, Gordon and Betty Moore Foundation, Brinson Foundation, Research Corporation for Science Advancement, California Institute of Technology, Texas Tech University, Canadian Institute for Advanced Research, University of Central Florida, Dunlap Institute for Astronomy and Astrophysics, University of Toronto, Oregon State University, Deutsche Forschungsgemeinschaft, University of British Columbia, Eötvös Loránd Tudományegyetem, Jet Propulsion Laboratory, Natural Sciences and Engineering Research Council of Canada, Science and Technology Facilities Council, Office of Naval Research, U.S. Naval Research Laboratory
Openalex Percentile: Top 9%
Pulsars and Gravitational Waves Research
3.46
DOIOpen Access PDFOpenAlex
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