2024/05/03 by Abhimanyu Susobhanan, D. L. Kaplan, Susobhanan, Abhimanyu +45 · 4 citations
Earth and Planetary Sciences · Physics and Astronomy · #FOS: Physical sciences #Geophysics and Gravity Measurements #High Energy Astrophysical Phenomena (astro-ph.HE) #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Pulsars and Gravitational Waves Research #Radio Astronomy Observations and Technology
paper · pdf · doi:10.48550/arxiv.2405.01977
openalex publication_date 2024/05/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 datasets. This framework enables the parameter estimation for both uncorrelated and correlated noise processes as well as the 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 datasets as well as a real dataset of PSR B1855+09. We also describe the new features implemented in PINT since it was first described in the literature.