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arxiv: 2508.16534 · v2 · submitted 2025-08-22 · 🌌 astro-ph.HE · astro-ph.CO· gr-qc

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The NANOGrav 15 yr Data Set: Targeted Searches for Supermassive Black Hole Binaries

Nikita Agarwal , Gabriella Agazie , Akash Anumarlapudi , Anne M. Archibald , Zaven Arzoumanian , Jeremy G. Baier , Paul T. Baker , Bence Becsy
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Laura Blecha Adam Brazier Paul R. Brook Sarah Burke-Spolaor Rand Burnette Robin Case J. Andrew Casey-Clyde Yu-Ting Chang Maria Charisi Shami Chatterjee Tyler Cohen Paolo Coppi James M. Cordes Neil J. Cornish Fronefield Crawford H. Thankful Cromartie Kathryn Crowter Megan E. DeCesar Paul B. Demorest Heling Deng Lankeswar Dey Timothy Dolch Daniel J. D'Orazio Ellis Eisenberg Elizabeth C. Ferrara William Fiore Emmanuel Fonseca Gabriel E. Freedman Emiko C. Gardiner Nate Garver-Daniels Peter A. Gentile Kyle A. Gersbach Joseph Glaser Matthew J. Graham Deborah C. Good Kayhan Gultekin C. J. Harris Jeffrey S. Hazboun Forrest Hutchison Ross J. Jennings Aaron D. Johnson Megan L. Jones David L. Kaplan Luke Zoltan Kelley Matthew Kerr Joey S. Key Nima Laal Michael T. Lam William G. Lamb Bjorn Larsen T. Joseph W. Lazio Natalia Lewandowska Tingting Liu Duncan R. Lorimer Jing Luo Ryan S. Lynch Chung-Pei Ma Dustin R. Madison Cayenne Matt Alexander McEwen James W. McKee Maura A. McLaughlin Natasha McMann Bradley W. Meyers Patrick M. Meyers Chiara M. F. Mingarelli Andrea Mitridate Priyamvada Natarajan Cherry Ng David J. Nice Stella Koch Ocker Ken D. Olum Timothy T. Pennucci Benetge B. P. Perera Polina Petrov Nihan S. Pol Henri A. Radovan Scott M. Ransom Paul S. Ray Joseph D. Romano Jessie C. Runnoe Alexander Saffer Shashwat C. Sardesai Ann Schmiedekamp Carl Schmiedekamp Kai Schmitz Federico Semenzato Brent J. Shapiro-Albert Rohan Shivakumar Xavier Siemens Joseph Simon Sophia V. Sosa Fiscella Ingrid H. Stairs Daniel R. Stinebring Kevin Stovall Abhimanyu Susobhanan Joseph K. Swiggum Jacob A. Taylor Stephen R. Taylor Mercedes S. Thompson Jacob E. Turner Michele Vallisneri Rutger van Haasteren Sarah J. Vigeland Haley M. Wahl London Willson Kevin P. Wilson Caitlin A. Witt David Wright Olivia Young Qinyuan Zheng
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classification 🌌 astro-ph.HE astro-ph.COgr-qc
keywords targetedcandidatesfactorsearchesbayesbinariesblackdata
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We present the first targeted searches for continuous gravitational waves (CWs) from 114 active galactic nuclei (AGN) that may host supermassive black hole binaries, using the NANOGrav 15 yr data set. By incorporating electromagnetic priors on sky location, distance, redshift, and CW frequency, our strain and chirp mass upper limits are typically improved by a factor of $\sim 2$ (median 2.2) relative to all-sky limits at the same frequency. Bayesian comparisons against a model including only a Hellings-Downs correlated background disfavors a CW signal for all targets, with a mean Bayes factor of $0.73 \pm 0.32$. Two targets have Bayes factors slightly above unity, but coherence tests, random targeting experiments, and a conservative accounting of the 114-target trials factor all indicate that they are consistent with noise. We use these two candidates as worked examples to illustrate an end-to-end targeted CW search analysis and a suite of follow up tests that future promising candidates would need to pass. We find that the electromagnetic interpretations of both candidates are ambiguous, and we update the constraints on a putative binary in 3C 66B, ruling out part of its previously allowed parameter space. Ultimately, our results demonstrate the current sensitivity of targeted pulsar timing array searches for CWs and define a roadmap for future multimessenger CW detections.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Gravity Echoes from Supermassive Black Hole Binaries

    astro-ph.HE 2026-04 unverdicted novelty 8.0

    Future microhertz detections combined with nanohertz pulsar terms can serve as gravity echoes to measure supermassive black hole binary inspiral rates from hundreds to thousands of years in the past.

  2. Scalable continuous gravitational wave detection in PTA data with non-parametric red noise suppression and optimal pulsar selection

    astro-ph.IM 2026-04 unverdicted novelty 6.0

    A frequentist CGW search method with non-parametric red noise suppression and optimal pulsar selection achieves Bayesian-comparable accuracy on NANOGrav-based simulations at far lower computational cost.