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The NANOGrav 15 yr Data Set: Running of the Spectral Index

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
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
Esmyol, David
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.
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
Santos, Rafael R. Lino dos
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
Schröder, Tobias
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
van Haasteren, Rutger
Vigeland, Sarah J.
von Eckardstein, Richard
Wahl, Haley M.
Witt, Caitlin A.
Wright, David
Young, Olivia
Publication Year :
2024

Abstract

The NANOGrav 15-year data provides compelling evidence for a stochastic gravitational-wave (GW) background at nanohertz frequencies. The simplest model-independent approach to characterizing the frequency spectrum of this signal consists in a simple power-law fit involving two parameters: an amplitude A and a spectral index \gamma. In this paper, we consider the next logical step beyond this minimal spectral model, allowing for a running (i.e., logarithmic frequency dependence) of the spectral index, \gamma_run(f) = \gamma + \beta \ln(f/f_ref). We fit this running-power-law (RPL) model to the NANOGrav 15-year data and perform a Bayesian model comparison with the minimal constant-power-law (CPL) model, which results in a 95% credible interval for the parameter \beta consistent with no running, \beta \in [-0.80,2.96], and an inconclusive Bayes factor, B(RPL vs. CPL) = 0.69 +- 0.01. We thus conclude that, at present, the minimal CPL model still suffices to adequately describe the NANOGrav signal; however, future data sets may well lead to a measurement of nonzero \beta. Finally, we interpret the RPL model as a description of primordial GWs generated during cosmic inflation, which allows us to combine our results with upper limits from big-bang nucleosynthesis, the cosmic microwave background, and LIGO-Virgo-KAGRA.<br />Comment: 17 pages, 4 figures, 2 tables

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2408.10166
Document Type :
Working Paper