Back to Search Start Over

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

Authors :
Agazie, Gabriella
Anumarlapudi, Akash
Archibald, Anne M.
Arzoumanian, Zaven
Baier, Jeremy George
Baker, Paul T.
Bécsy, Bence
Blecha, Laura
Brazier, Adam
Brook, Paul R.
Burke-Spolaor, Sarah
Casey-Clyde, J. Andrew
Charisi, Maria
Chatterjee, Shami
Chatziioannou, Katerina
Cohen, Tyler
Cordes, James M.
Cornish, Neil J.
Crawford, Fronefield
Cromartie, H. Thankful
Crowter, Kathryn
DeCesar, Megan E.
Demorest, Paul B.
Deng, Heling
Dey, Lankeswar
Dolch, Timothy
Ferrara, Elizabeth C.
Fiore, William
Fonseca, Emmanuel
Freedman, Gabriel E.
Gardiner, Emiko C.
Garver-Daniels, Nate
Gentile, Peter A.
Gersbach, Kyle A.
Glaser, Joseph
Good, Deborah C.
Gültekin, Kayhan
Hazboun, Jeffrey S.
Jennings, Ross J.
Johnson, Aaron D.
Jones, Megan L.
Kaiser, Andrew R.
Kaplan, David L.
Kelley, Luke Zoltan
Kerr, Matthew
Key, Joey S.
Laal, Nima
Lam, Michael T.
Lamb, William G.
Larsen, Bjorn
Lazio, T. Joseph W.
Lewandowska, Natalia
Liu, Tingting
Lorimer, Duncan R.
Luo, Jing
Lynch, Ryan S.
Ma, Chung-Pei
Madison, Dustin R.
McEwen, Alexander
McKee, James W.
McLaughlin, Maura A.
McMann, Natasha
Meyers, Bradley W.
Meyers, Patrick M.
Mingarelli, Chiara M. F.
Mitridate, Andrea
Ng, Cherry
Nice, David J.
Ocker, Stella Koch
Olum, Ken D.
Pennucci, Timothy T.
Perera, Benetge B. P.
Pol, Nihan S.
Radovan, Henri A.
Ransom, Scott M.
Ray, Paul S.
Romano, Joseph D.
Runnoe, Jessie C.
Saffer, Alexander
Sardesai, Shashwat C.
Schmiedekamp, Ann
Schmiedekamp, Carl
Schmitz, Kai
Shapiro-Albert, Brent J.
Siemens, Xavier
Simon, Joseph
Siwek, Magdalena S.
Fiscella, Sophia V. Sosa
Stairs, Ingrid H.
Stinebring, Daniel R.
Stovall, Kevin
Susobhanan, Abhimanyu
Swiggum, Joseph K.
Taylor, Stephen R.
Turner, Jacob E.
Unal, Caner
Vallisneri, Michele
Vigeland, Sarah J.
Wahl, Haley M.
Witt, Caitlin A.
Wright, David
Young, Olivia
Publication Year :
2024

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. Those 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 are idealizations that 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, and use them to assess whether the optimal-statistic significance, inter-pulsar correlations, and spectral coefficients assume extreme values for the real data when compared to the replications. We confirm that the NANOGrav 15 yr data set is consistent with power-law and Hellings--Downs assumptions. 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 as reported by NANOGrav.<br />Comment: 20 pages, 14 Figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2407.20510
Document Type :
Working Paper