PINT: Maximum-likelihood Estimation of Pulsar Timing Noise Parameters

PINT: Maximum-likelihood Estimation of Pulsar Timing Noise Parameters

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 processe...

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Detalles Bibliográficos
Main Authors: Abhimanyu Susobhanan, David L. Kaplan, Anne M. Archibald, Jing Luo, Paul S. Ray, Timothy T. Pennucci, Scott M. Ransom, Gabriella Agazie, William Fiore, Bjorn Larsen, Patrick O’Neill, Rutger van Haasteren, Akash Anumarlapudi, Matteo Bachetti, Deven Bhakta, Chloe A. Champagne, H. Thankful Cromartie, Paul B. Demorest, Ross J. Jennings, Matthew Kerr, Sasha Levina, Alexander McEwen, Brent J. Shapiro-Albert, Joseph K. Swiggum
Formato: Artigo
Idioma:English
Publicado: IOP Publishing 2024-01-01
Series:The Astrophysical Journal
Subjects:
Pulsars
Astronomy software
Astronomy data analysis
Acceso en liña:https://doi.org/10.3847/1538-4357/ad59f7

Internet

https://doi.org/10.3847/1538-4357/ad59f7

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