1. The NANOGrav 15 yr Data Set: Running of the Spectral Index
- Author
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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, and Young, Olivia
- Subjects
Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Cosmology and Nongalactic Astrophysics ,General Relativity and Quantum Cosmology ,High Energy Physics - Phenomenology - 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., Comment: 17 pages, 4 figures, 2 tables
- Published
- 2024