JUG: JAX-based Unified pulsar timinG

[2608.27786] JUG: JAX-based Unified pulsar timinG Skip to main content Search Submit Donate Log in Astrophysics > Instrumentation and Methods for Astrophysics arXiv:2608.27786 (astro-ph) [Submitted on 27 Aug 2026] Title: JUG: JAX-based Unified pulsar timinG Authors: Matthew T. Miles , Stephen R. Taylor , Matthew Bailes , Aurelien Chalumeau , H. Thankful Cromartie , Kyle A. Gersbach , Rutger van Haasteren , Michael J. Keith , Nima Laal , Michael T. Lam , Kuo Liu , Aditya Parthasarathy , Scott M. Ransom , Daniel J. Reardon , Ryan M. Shannon , David C. Wright , Andrew Zic View PDF HTML (experimental) Abstract: We present JUG (JAX-based Unified pulsar timinG), a JAX-based, fully independent pulsar timing package emphasising speed and ease of use, designed to confidently handle the increasingly large and complex pulsar timing array datasets that are being created in the pulsar timing field. JUG implements the entire pulsar timing pipeline itself, from data handling and clock corrections through to the timing model and fitting, without relying on other timing software. It enables Pythonic programming at the speed of compiled code, is GPU-capable, and can be operated via a Python API or an interactive GUI. A user of JUG can interactively explore data, fit timing models with complex stochastic noise, model deterministic signals such as continuous gravitational waves, and obtain accurate point estimates of the parameters of the stochastic processes present, thereby bridging frequentist timing and Bayesian noise analysis. JUG is faster than PINT by more than fifty times and is comparably fast to Tempo2, can handle millions of arrival times, agrees with PINT at the picosecond level, and can reliably recover known timing model and noise parameter values. In this paper we describe its design, performance, and validation, and demonstrate its advantages for pulsar timing data analysis. Subjects: Instrumentation and Methods for Astrophysics (astro-ph.IM) ; High Energy Astrophysical Phenomena (astro-ph.HE) Cite as: arXiv:2608.27786 [astro-ph.IM] (or arXiv:2608.27786v1 [astro-ph.IM] for this version) https://doi.org/10.48550/arXiv.2608.27786 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Matthew Miles Mr [ view email ] [v1] Thu, 27 Aug 2026 23:48:12 UTC (2,355 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: astro-ph.IM < prev | next > new | recent | 2026-08 Change to browse by: astro-ph astro-ph.HE References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) IArxiv recommender toggle IArxiv Recommender ( What is IArxiv? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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