Accès ouvert déclaré
2024
preprint
The NANOGrav 15 Yr Data Set: Removing Pulsars One by One from the Pulsar Timing Array
Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, J. G. Baier, P. T. Baker, B. Bécsy, Laura Blecha, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, J. Andrew Casey-Clyde, Maria Charisi, Shami Chatterjee, Tyler Cohen, J. M. Cordes, Neil J. Cornish, F. Crawford, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Paul B. Demorest, Heling Deng, Lankeswar Dey, Timothy Dolch, E. 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, L. Guertin, Kayhan Gültekin, Jeffrey S. Hazboun, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, Andrew R. Kaiser, D. L. Kaplan, Luke Zoltan Kelley, M. Kerr, J. S. Key, Nima Laal, Michael T. Lam, William G. Lamb, Bjorn Larsen, T. Joseph W. Lazio, N. Lewandowska, Tingting Liu, D. R. Lorimer, Jing Luo, Ryan S. Lynch, Chung‐Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, M. A. McLaughlin, Natasha McMann, Bradley W. Meyers, P. M. Meyers, H. Middleton, 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, H. A. Radovan, S. 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, I. H. Stairs, Daniel R. Stinebring, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Stephen R. Taylor, Jacob E. Turner, Caner Ünal, Michele Vallisneri, A. Vecchio, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, David Wright, Olivia Young
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Le résumé fourni par la source
Evidence has emerged for a stochastic signal correlated among 67 pulsars within the 15-year pulsar-timing data set compiled by the NANOGrav collaboration. Similar signals have been found in data from the European, Indian, Parkes, and Chinese PTAs. This signal has been interpreted as indicative of the presence of a nanohertz stochastic gravitational wave background. To explore the internal consistency of this result we investigate how the recovered signal strength changes as we remove the pulsars one by one from the data set. We calculate the signal strength using the (noise-marginalized) optimal statistic, a frequentist metric designed to measure correlated excess power in the residuals of the arrival times of the radio pulses. We identify several features emerging from this analysis that were initially unexpected. The significance of these features, however, can only be assessed by comparing the real data to synthetic data sets. After conducting identical analyses on simulated data sets, we do not find anything inconsistent with the presence of a stochastic gravitational wave background in the NANOGrav 15-year data. The methodologies developed here can offer additional tools for application to future, more sensitive data sets. While this analysis provides an internal consistency check of the NANOGrav results, it does not eliminate the necessity for additional investigations that could identify potential systematics or uncover unmodeled physical phenomena in the data.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
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Les sujets associés
Pulsars and Gravitational Waves ResearchGeophysics and Gravity MeasurementsSeismology and Earthquake Studies