Details
| Original language | English |
|---|---|
| Article number | 150 |
| Number of pages | 20 |
| Journal | Astrophysical Journal |
| Volume | 971 |
| Issue number | 2 |
| Publication status | Published - 14 Aug 2024 |
Abstract
PINT is a pure-Python framework for high-precision pulsar timing developed on top of widely used and well-tested Python libraries, supporting both interactive and programmatic data analysis workflows. We present a new frequentist framework within PINT to characterize the single-pulsar noise processes present in pulsar timing data sets. This framework enables parameter estimation for both uncorrelated and correlated noise processes, as well as model comparison between different timing and noise models in a computationally inexpensive way. We demonstrate the efficacy of the new framework by applying it to simulated data sets as well as a real data set of PSR B1855+09. We also describe the new features implemented in PINT since it was first described in the literature.
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Astronomy and Astrophysics
- Earth and Planetary Sciences(all)
- Space and Planetary Science
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In: Astrophysical Journal, Vol. 971, No. 2, 150, 14.08.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - PINT
T2 - Maximum-likelihood Estimation of Pulsar Timing Noise Parameters
AU - Susobhanan, Abhimanyu
AU - Kaplan, David L.
AU - Archibald, Anne M.
AU - Luo, Jing
AU - Ray, Paul S.
AU - Pennucci, Timothy T.
AU - Ransom, Scott M.
AU - Agazie, Gabriella
AU - Fiore, William
AU - Larsen, Bjorn
AU - O’Neill, Patrick
AU - van Haasteren, Rutger
AU - Anumarlapudi, Akash
AU - Bachetti, Matteo
AU - Bhakta, Deven
AU - Champagne, Chloe A.
AU - Cromartie, H. Thankful
AU - Demorest, Paul B.
AU - Jennings, Ross J.
AU - Kerr, Matthew
AU - Levina, Sasha
AU - McEwen, Alexander
AU - Shapiro-Albert, Brent J.
AU - Swiggum, Joseph K.
N1 - Publisher Copyright: © 2024. The Author(s). Published by the American Astronomical Society.
PY - 2024/8/14
Y1 - 2024/8/14
N2 - PINT is a pure-Python framework for high-precision pulsar timing developed on top of widely used and well-tested Python libraries, supporting both interactive and programmatic data analysis workflows. We present a new frequentist framework within PINT to characterize the single-pulsar noise processes present in pulsar timing data sets. This framework enables parameter estimation for both uncorrelated and correlated noise processes, as well as model comparison between different timing and noise models in a computationally inexpensive way. We demonstrate the efficacy of the new framework by applying it to simulated data sets as well as a real data set of PSR B1855+09. We also describe the new features implemented in PINT since it was first described in the literature.
AB - PINT is a pure-Python framework for high-precision pulsar timing developed on top of widely used and well-tested Python libraries, supporting both interactive and programmatic data analysis workflows. We present a new frequentist framework within PINT to characterize the single-pulsar noise processes present in pulsar timing data sets. This framework enables parameter estimation for both uncorrelated and correlated noise processes, as well as model comparison between different timing and noise models in a computationally inexpensive way. We demonstrate the efficacy of the new framework by applying it to simulated data sets as well as a real data set of PSR B1855+09. We also describe the new features implemented in PINT since it was first described in the literature.
UR - http://www.scopus.com/inward/record.url?scp=85201306400&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2405.01977
DO - 10.48550/arXiv.2405.01977
M3 - Article
AN - SCOPUS:85201306400
VL - 971
JO - Astrophysical Journal
JF - Astrophysical Journal
SN - 0004-637X
IS - 2
M1 - 150
ER -