How to Detect an Astrophysical Nanohertz Gravitational Wave Background

Date

2023-12-01

Author

Becsy, Bence
Cornish, Neil J.
Meyers, Patrick M.
Kelley, Luke Zoltan
Agazie, Gabriella
Anumarlapudi, Akash
Archibald, Anne M.
Arzoumanian, Zaven
Baker, Paul T.
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.
Crawford, Fronefield
Cromartie, H. Thankful
Crowter, Kathryn
Decesar, Megan E.
Demorest, Paul B.
Dolch, Timothy
Ferrara, Elizabeth C.
Fiore, William
Fonseca, Emmanuel
Freedman, Gabriel E.
Garver-Daniels, Nate
Gentile, Peter A.
Glaser, Joseph
Good, Deborah C.
Gueltekin, Kayhan
Hazboun, Jeffrey S.
Hourihane, Sophie
Jennings, Ross J.
Johnson, Aaron D.
Jones, Megan L.
Kaiser, Andrew R.
Kaplan, David L.
Kerr, Matthew
Key, Joey S.
Laal, Nima
Lam, Michael T.
Lamb, William G.
W. Lazio, T. Joseph
Lewandowska, Natalia
Littenberg, Tyson B.
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.
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.
Sardesai, Shashwat C.
Schmiedekamp, Ann
Schmiedekamp, Carl
Schmitz, Kai
Shapiro-Albert, Brent J.
Siemens, Xavier
Simon, Joseph
Siwek, Magdalena S.
Sosa Fiscella, Sophia V.
Stairs, Ingrid H.
Stinebring, Daniel R.
Stovall, Kevin
Susobhanan, Abhimanyu
Swiggum, Joseph K.
Taylor, Stephen R.
Turner, Jacob E.
Ünal, Caner
Vallisneri, Michele
van Haasteren, Rutger
Vigeland, Sarah J.
Wahl, Haley M.
Witt, Caitlin A.
Young, Olivia

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Analyses of pulsar timing data have provided evidence for a stochastic gravitational wave background in the nanohertz frequency band. The most plausible source of this background is the superposition of signals from millions of supermassive black hole binaries. The standard statistical techniques used to search for this background and assess its significance make several simplifying assumptions, namely (i) Gaussianity, (ii) isotropy, and most often, (iii) a power-law spectrum. However, a stochastic background from a finite collection of binaries does not exactly satisfy any of these assumptions. To understand the effect of these assumptions, we test standard analysis techniques on a large collection of realistic simulated data sets. The data-set length, observing schedule, and noise levels were chosen to emulate the NANOGrav 15 yr data set. Simulated signals from millions of binaries drawn from models based on the Illustris cosmological hydrodynamical simulation were added to the data. We find that the standard statistical methods perform remarkably well on these simulated data sets, even though their fundamental assumptions are not strictly met. They are able to achieve a confident detection of the background. However, even for a fixed set of astrophysical parameters, different realizations of the universe result in a large variance in the significance and recovered parameters of the background. We also find that the presence of loud individual binaries can bias the spectral recovery of the background if we do not account for them.

URI

https://hdl.handle.net/11511/115837

Collections

Department of Physics, Article