JUG: JAX-based Unified pulsar timinG

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.

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Cite

BibTeX RIS

BibTeX

@misc{miles2026jaxbased,
  title = {{JUG: JAX-based Unified pulsar timinG}},
  author = {Matthew T. Miles and Stephen R. Taylor and Matthew Bailes and Aurelien Chalumeau and H. Thankful Cromartie and Kyle A. Gersbach and Rutger van Haasteren and Michael J. Keith and Nima Laal and Michael T. Lam and Kuo Liu and Aditya Parthasarathy and Scott M. Ransom and Daniel J. Reardon and Ryan M. Shannon and David C. Wright and Andrew Zic},
  howpublished = {arXiv},
  year = {2026},
  month = aug,
  doi = {10.48550/arxiv.2608.27786},
  eprint = {2608.27786},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.27786},
}

RIS

TY  - UNPB
TI  - JUG: JAX-based Unified pulsar timinG
AU  - Matthew T. Miles
AU  - Stephen R. Taylor
AU  - Matthew Bailes
AU  - Aurelien Chalumeau
AU  - H. Thankful Cromartie
AU  - Kyle A. Gersbach
AU  - Rutger van Haasteren
AU  - Michael J. Keith
AU  - Nima Laal
AU  - Michael T. Lam
AU  - Kuo Liu
AU  - Aditya Parthasarathy
AU  - Scott M. Ransom
AU  - Daniel J. Reardon
AU  - Ryan M. Shannon
AU  - David C. Wright
AU  - Andrew Zic
PY  - 2026
DA  - 2026/08/27
PB  - arXiv
DO  - 10.48550/arxiv.2608.27786
UR  - https://arxiv.org/abs/2608.27786
AB  - 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.
ER  -

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