Gabriella Agazie
The NANOGrav 12.5 yr Data Set: A Computationally Efficient Eccentric Binary Search Pipeline and Constraints on an Eccentric Supermassive Binary Candidate in 3C 66B
Agazie, Gabriella; Arzoumanian, Zaven; Baker, Paul T.; Bécsy, Bence; Blecha, Laura; Blumer, Harsha; Brazier, Adam; Brook, Paul R.; Burke-Spolaor, Sarah; Casey-Clyde, J. Andrew; Charisi, Maria; Chatterjee, Shami; Cheeseboro, Belinda D.; Cohen, Tyler; Cordes, James M.; Cornish, Neil J.; Crawford, Fronefield; Cromartie, H. Thankful; DeCesar, Megan E.; Demorest, Paul B.; Dey, Lankeswar; Dolch, Timothy; Ellis, Justin A.; Ferdman, Robert D.; Ferrara, Elizabeth C.; Fiore, William; Fonseca, Emmanuel; Freedman, Gabriel E.; Garver-Daniels, Nate; Gentile, Peter A.; Glaser, Joseph; Good, Deborah C.; Gopakumar, Achamveedu; Gültekin, Kayhan; Hazboun, Jeffrey S.; Jennings, Ross J.; Johnson, Aaron D.; Jones, Megan L.; Kaiser, Andrew R.; Kaplan, David L.; Kelley, Luke Zoltan; Key, Joey S.; Laal, Nima; Lam, Michael T.; Lamb, William G.; W. Lazio, T. Joseph; Lewandowska, Natalia; Liu, Tingting; Lorimer, Duncan R.; Luo, Jing; Lynch, Ryan S.; Ma, Chung Pei; Madison, Dustin R.; McEwen, Alexander; McKee, Jam...
Authors
Zaven Arzoumanian
Paul T. Baker
Bence Bécsy
Laura Blecha
Harsha Blumer
Adam Brazier
Paul R. Brook
Sarah Burke-Spolaor
J. Andrew Casey-Clyde
Maria Charisi
Shami Chatterjee
Belinda D. Cheeseboro
Tyler Cohen
James M. Cordes
Neil J. Cornish
Fronefield Crawford
H. Thankful Cromartie
Megan E. DeCesar
Paul B. Demorest
Lankeswar Dey
Timothy Dolch
Justin A. Ellis
Robert D. Ferdman
Elizabeth C. Ferrara
William Fiore
Emmanuel Fonseca
Gabriel E. Freedman
Nate Garver-Daniels
Peter A. Gentile
Joseph Glaser
Deborah C. Good
Achamveedu Gopakumar
Kayhan Gültekin
Jeffrey S. Hazboun
Ross J. Jennings
Aaron D. Johnson
Megan L. Jones
Andrew R. Kaiser
David L. Kaplan
Luke Zoltan Kelley
Joey S. Key
Nima Laal
Michael T. Lam
William G. Lamb
T. Joseph W. Lazio
Natalia Lewandowska
Tingting Liu
Duncan R. Lorimer
Jing Luo
Ryan S. Lynch
Chung Pei Ma
Dustin R. Madison
Alexander McEwen
James W. McKee
Maura A. McLaughlin
Patrick M. Meyers
Chiara M.F. Mingarelli
Andrea Mitridate
Cherry Ng
David J. Nice
Stella Koch Ocker
Ken D. Olum
Timothy T. Pennucci
Nihan S. Pol
Henri A. Radovan
Scott M. Ransom
Paul S. Ray
Joseph D. Romano
Shashwat C. Sardesai
Kai Schmitz
Xavier Siemens
Joseph Simon
Magdalena S. Siwek
Sophia V. Sosa Fiscella
Renée Spiewak
Ingrid H. Stairs
Daniel R. Stinebring
Kevin Stovall
Abhimanyu Susobhanan
Joseph K. Swiggum
Stephen R. Taylor
Jacob E. Turner
Caner Unal
Michele Vallisneri
Sarah J. Vigeland
Caitlin A. Witt
Olivia Young
The NANOGrav Collaboration
Abstract
The radio galaxy 3C 66B has been hypothesized to host a supermassive black hole binary (SMBHB) at its center based on electromagnetic observations. Its apparent 1.05 yr period and low redshift (∼0.02) make it an interesting testbed to search for low-frequency gravitational waves (GWs) using pulsar timing array (PTA) experiments. This source has been subjected to multiple searches for continuous GWs from a circular SMBHB, resulting in progressively more stringent constraints on its GW amplitude and chirp mass. In this paper, we develop a pipeline for performing Bayesian targeted searches for eccentric SMBHBs in PTA data sets, and test its efficacy by applying it to simulated data sets with varying injected signal strengths. We also search for a realistic eccentric SMBHB source in 3C 66B using the NANOGrav 12.5 yr data set employing PTA signal models containing Earth term-only as well as Earth+pulsar term contributions using this pipeline. Due to limitations in our PTA signal model, we get meaningful results only when the initial eccentricity e 0 < 0.5 and the symmetric mass ratio η > 0.1. We find no evidence for an eccentric SMBHB signal in our data, and therefore place 95% upper limits on the PTA signal amplitude of 88.1 ± 3.7 ns for the Earth term-only and 81.74 ± 0.86 ns for the Earth+pulsar term searches for e 0 < 0.5 and η > 0.1. Similar 95% upper limits on the chirp mass are (1.98 ± 0.05) × 109 and (1.81 ± 0.01) × 109 M ☉. These upper limits, while less stringent than those calculated from a circular binary search in the NANOGrav 12.5 yr data set, are consistent with the SMBHB model of 3C 66B developed from electromagnetic observations.
Citation
Agazie, G., Arzoumanian, Z., Baker, P. T., Bécsy, B., Blecha, L., Blumer, H., Brazier, A., Brook, P. R., Burke-Spolaor, S., Casey-Clyde, J. A., Charisi, M., Chatterjee, S., Cheeseboro, B. D., Cohen, T., Cordes, J. M., Cornish, N. J., Crawford, F., Cromartie, H. T., DeCesar, M. E., Demorest, P. B., …The NANOGrav Collaboration. (2024). The NANOGrav 12.5 yr Data Set: A Computationally Efficient Eccentric Binary Search Pipeline and Constraints on an Eccentric Supermassive Binary Candidate in 3C 66B. The Astrophysical journal, 963(2), 144. https://doi.org/10.3847/1538-4357/ad1f61
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 15, 2024 |
Online Publication Date | Mar 7, 2024 |
Publication Date | Mar 1, 2024 |
Deposit Date | Mar 11, 2024 |
Publicly Available Date | Mar 12, 2024 |
Journal | Astrophysical Journal |
Print ISSN | 0004-637X |
Electronic ISSN | 1538-4357 |
Publisher | American Astronomical Society |
Peer Reviewed | Peer Reviewed |
Volume | 963 |
Issue | 2 |
Pages | 144 |
DOI | https://doi.org/10.3847/1538-4357/ad1f61 |
Keywords | Space and Planetary Science; Astronomy and Astrophysics |
Public URL | https://hull-repository.worktribe.com/output/4586418 |
Additional Information | Article Title: The NANOGrav 12.5 yr Data Set: A Computationally Efficient Eccentric Binary Search Pipeline and Constraints on an Eccentric Supermassive Binary Candidate in 3C 66B; Journal Title: The Astrophysical Journal; Article Type: paper; Copyright Information: © 2024. The Author(s). Published by the American Astronomical Society.; Date Received: 2023-09-27; Date Accepted: 2024-01-15; Online publication date: 2024-03-07 |
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Copyright Statement
© 2024. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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