{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/bayesian-insights-into-post-glitch-dynamics","title":"Bayesian Insights into post-Glitch Dynamics: Model comparison and parameter constraint from decades long observation data of the Crab pulsar","arxiv_id":"2409.18432","date":"2024-09-27","proceeding":null,"authors":["Chun Huang","Xiao-Ping Zheng"],"abstract":"The Crab Pulsar has exhibited numerous glitches accompanied by persistent shifts in its spin-down rate. The explanation of the observed persistent shifts remain a challenge. We perform a detailed Bayesian analysis to compare four data-fitting models, ranging from a simple linear model to more complex power-law and logarithmic models, using a dataset of observed glitches and persistent shifts. Our results show the large observed events are difficult to explain by the usually assumed linear model due to starquakes. A particularly notable finding is that the logarithmic model provides the best fit to the observation data but the two power-law models show a close tie to it. Detail differences of these models may be further clarified by the understanding of internal physics of neutron stars.","url_abs":"https://arxiv.org/abs/2409.18432v1","url_pdf":"https://arxiv.org/pdf/2409.18432v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"bayesian-insights-into-post-glitch-dynamics","repo_url":"https://github.com/chunhuangphy/compactobject","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"bayesian-insights-into-post-glitch-dynamics","repo_url":"https://github.com/chunhuangphy/compactoject","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}