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arxiv: 2407.20510 · v2 · pith:YX6FEZNRnew · submitted 2024-07-30 · 🌌 astro-ph.HE · gr-qc

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

Gabriella Agazie , Akash Anumarlapudi , Anne M. Archibald , Zaven Arzoumanian , Jeremy George Baier , Paul T. Baker , Bence B\'ecsy , Laura Blecha
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Adam Brazier Paul R. Brook Sarah Burke-Spolaor J. Andrew Casey-Clyde Maria Charisi Shami Chatterjee Katerina Chatziioannou 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 Kayhan G\"ultekin 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 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 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 Sarah J. Vigeland Haley M. Wahl Caitlin A. Witt David Wright Olivia Young
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classification 🌌 astro-ph.HE gr-qc
keywords databackgroundcorrelationsnanogravpulsarreplicationssignificanceacross
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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 data set using Bayesian posterior predictive checks. After fitting our fiducial model to real data, we generate a population of simulated data-set replications. We use the replications to assess whether the optimal-statistic significance, inter-pulsar correlations, and spectral coefficients are extreme. We recover Hellings--Downs correlations in simulated data sets at significance levels consistent with the correlations measured in the NANOGrav 15 yr data set. 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 $\sigma$ and 3 $\sigma$ 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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