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NANOGrav 15-year gravitational-wave background methods

Johnson, Aaron D.; Meyers, Patrick M.; Baker, Paul T.; Cornish, Neil J.; Hazboun, Jeffrey S.; Littenberg, Tyson B.; Romano, Joseph D.; Taylor, Stephen R.; Vallisneri, Michele; Vigeland, Sarah J.; Olum, Ken D.; Siemens, Xavier; Ellis, Justin A.; Van Haasteren, Rutger; Hourihane, Sophie; Agazie, Gabriella; Anumarlapudi, Akash; Archibald, Anne M.; Arzoumanian, Zaven; Blecha, Laura; Brazier, Adam; Brook, Paul R.; Burke-Spolaor, Sarah; Bécsy, Bence; Casey-Clyde, J. Andrew; Charisi, Maria; Chatterjee, Shami; Chatziioannou, Katerina; Cohen, Tyler; Cordes, James M.; Crawford, Fronefield; Cromartie, H. Thankful; Crowter, Kathryn; Decesar, Megan E.; Demorest, Paul B.; Dolch, Timothy; Drachler, Brendan; Ferrara, Elizabeth C.; Fiore, William; Fonseca, Emmanuel; Freedman, Gabriel E.; Garver-Daniels, Nate; Gentile, Peter A.; Glaser, Joseph; Good, Deborah C.; Gültekin, Kayhan; Jennings, Ross J.; Jones, Megan L.; Kaiser, Andrew R.; Kaplan, David L.; Kelley, Luke Zoltan; Kerr, Matthew; Key, Joey S.; La...

Authors

Aaron D. Johnson

Patrick M. Meyers

Paul T. Baker

Neil J. Cornish

Jeffrey S. Hazboun

Tyson B. Littenberg

Joseph D. Romano

Stephen R. Taylor

Michele Vallisneri

Sarah J. Vigeland

Ken D. Olum

Xavier Siemens

Justin A. Ellis

Rutger Van Haasteren

Sophie Hourihane

Gabriella Agazie

Akash Anumarlapudi

Anne M. Archibald

Zaven Arzoumanian

Laura Blecha

Adam Brazier

Paul R. Brook

Sarah Burke-Spolaor

Bence Bécsy

J. Andrew Casey-Clyde

Maria Charisi

Shami Chatterjee

Katerina Chatziioannou

Tyler Cohen

James M. Cordes

Fronefield Crawford

H. Thankful Cromartie

Kathryn Crowter

Megan E. Decesar

Paul B. Demorest

Timothy Dolch

Brendan Drachler

Elizabeth C. Ferrara

William Fiore

Emmanuel Fonseca

Gabriel E. Freedman

Nate Garver-Daniels

Peter A. Gentile

Joseph Glaser

Deborah C. Good

Kayhan Gültekin

Ross J. Jennings

Megan L. Jones

Andrew R. Kaiser

David L. Kaplan

Luke Zoltan Kelley

Matthew Kerr

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

Maura A. McLaughlin

Natasha McMann

Bradley W. Meyers

Chiara M.F. Mingarelli

Andrea Mitridate

Cherry Ng

David J. Nice

Stella Koch Ocker

Timothy T. Pennucci

Benetge B.P. Perera

Nihan S. Pol

Henri A. Radovan

Scott M. Ransom

Paul S. Ray

Shashwat C. Sardesai

Carl Schmiedekamp

Ann Schmiedekamp

Kai Schmitz

Brent J. Shapiro-Albert

Joseph Simon

Magdalena S. Siwek

Ingrid H. Stairs

Daniel R. Stinebring

Kevin Stovall

Abhimanyu Susobhanan

Joseph K. Swiggum

Jacob E. Turner

Caner Unal

Haley M. Wahl

Caitlin A. Witt

Olivia Young



Abstract

Pulsar timing arrays (PTAs) use an array of millisecond pulsars to search for gravitational waves in the nanohertz regime in pulse time of arrival data. This paper presents rigorous tests of PTA methods, examining their consistency across the relevant parameter space. We discuss updates to the 15-year isotropic gravitational-wave background analyses and their corresponding code representations. Descriptions of the internal structure of the flagship algorithms enterprise and ptmcmcsampler are given to facilitate understanding of the PTA likelihood structure, how models are built, and what methods are currently used in sampling the high-dimensional PTA parameter space. We introduce a novel version of the PTA likelihood that uses a two-step marginalization procedure that performs much faster in gravitational wave searches, reducing the required resources facilitating the computation of Bayes factors via thermodynamic integration and sampling a large number of realizations for computing Bayesian false-alarm probabilities. We perform stringent tests of consistency and correctness of the Bayesian and frequentist analysis methods. For the Bayesian analysis, we test prior recovery, simulation recovery, and Bayes factors. For the frequentist analysis, we test that the optimal statistic, when modified to account for a non-negligible gravitational-wave background, accurately recovers the amplitude of the background. We also summarize recent advances and tests performed on the optimal statistic in the literature from both gravitational wave background detection and parameter estimation perspectives. The tests presented here validate current analyses of PTA data.

Citation

Johnson, A. D., Meyers, P. M., Baker, P. T., Cornish, N. J., Hazboun, J. S., Littenberg, T. B., …Young, O. (2024). NANOGrav 15-year gravitational-wave background methods. Physical Review D, 109(10), Article 103012. https://doi.org/10.1103/PhysRevD.109.103012

Journal Article Type Article
Acceptance Date Mar 21, 2024
Online Publication Date May 9, 2024
Publication Date May 15, 2024
Deposit Date May 23, 2024
Publicly Available Date May 28, 2024
Journal Physical Review D
Print ISSN 2470-0010
Electronic ISSN 2470-0029
Publisher American Physical Society
Peer Reviewed Peer Reviewed
Volume 109
Issue 10
Article Number 103012
DOI https://doi.org/10.1103/PhysRevD.109.103012
Public URL https://hull-repository.worktribe.com/output/4672922

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