The NANOGrav 15-year Gravitational-Wave Background Methods
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arXiv
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| Natura: | Preprint |
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2023
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| author | 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. Laal, Nima Lam, Michael T. Lamb, William G. Lazio, T. Joseph W. Lewandowska, Natalia Liu, Tingting Lorimer, Duncan R. Lynch, Ryan S. Ma, Chung-Pei Madison, Dustin R. McEwen, Alexander McKee, James W. McLaughlin, Maura A. McMann, Natasha Meyers, Bradley W. Mingarelli, Chiara M. F. Mitridate, Andrea Ng, Cherry Nice, David J. Ocker, Stella Koch Pennucci, Timothy T. Perera, Benetge B. P. Pol, Nihan S. Radovan, Henri A. Ransom, Scott M. Ray, Paul S. Sardesai, Shashwat C. Schmiedekamp, Carl Schmiedekamp, Ann Schmitz, Kai Shapiro-Albert, Brent J. Simon, Joseph Siwek, Magdalena S. Stairs, Ingrid H. Stinebring, Daniel R. Stovall, Kevin Susobhanan, Abhimanyu Swiggum, Joseph K. Turner, Jacob E. Unal, Caner Wahl, Haley M. Witt, Caitlin A. Young, Olivia |
| author_facet | 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. Laal, Nima Lam, Michael T. Lamb, William G. Lazio, T. Joseph W. Lewandowska, Natalia Liu, Tingting Lorimer, Duncan R. Lynch, Ryan S. Ma, Chung-Pei Madison, Dustin R. McEwen, Alexander McKee, James W. McLaughlin, Maura A. McMann, Natasha Meyers, Bradley W. Mingarelli, Chiara M. F. Mitridate, Andrea Ng, Cherry Nice, David J. Ocker, Stella Koch Pennucci, Timothy T. Perera, Benetge B. P. Pol, Nihan S. Radovan, Henri A. Ransom, Scott M. Ray, Paul S. Sardesai, Shashwat C. Schmiedekamp, Carl Schmiedekamp, Ann Schmitz, Kai Shapiro-Albert, Brent J. Simon, Joseph Siwek, Magdalena S. Stairs, Ingrid H. Stinebring, Daniel R. Stovall, Kevin Susobhanan, Abhimanyu Swiggum, Joseph K. Turner, Jacob E. Unal, Caner Wahl, Haley M. Witt, Caitlin A. Young, Olivia |
| contents | 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 GWB detection and parameter estimation perspectives. The tests presented here validate current analyses of PTA data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_16223 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | The 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. Laal, Nima Lam, Michael T. Lamb, William G. Lazio, T. Joseph W. Lewandowska, Natalia Liu, Tingting Lorimer, Duncan R. Lynch, Ryan S. Ma, Chung-Pei Madison, Dustin R. McEwen, Alexander McKee, James W. McLaughlin, Maura A. McMann, Natasha Meyers, Bradley W. Mingarelli, Chiara M. F. Mitridate, Andrea Ng, Cherry Nice, David J. Ocker, Stella Koch Pennucci, Timothy T. Perera, Benetge B. P. Pol, Nihan S. Radovan, Henri A. Ransom, Scott M. Ray, Paul S. Sardesai, Shashwat C. Schmiedekamp, Carl Schmiedekamp, Ann Schmitz, Kai Shapiro-Albert, Brent J. Simon, Joseph Siwek, Magdalena S. Stairs, Ingrid H. Stinebring, Daniel R. Stovall, Kevin Susobhanan, Abhimanyu Swiggum, Joseph K. Turner, Jacob E. Unal, Caner Wahl, Haley M. Witt, Caitlin A. Young, Olivia High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology 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 GWB detection and parameter estimation perspectives. The tests presented here validate current analyses of PTA data. |
| title | The NANOGrav 15-year Gravitational-Wave Background Methods |
| topic | High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology |
| url | https://arxiv.org/abs/2306.16223 |