{"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/kalkayotl-2-0-bayesian-phase-space-modelling","title":"Kalkayotl 2.0 Bayesian phase-space modelling of star-forming regions, stellar associations, and open clusters","arxiv_id":"2411.16012","date":"2024-11-24","proceeding":null,"authors":["J. Olivares","H. Bouy","Trevor Z. Dorn-Wallenstein","A. Berihuete"],"abstract":"Context: Star-forming regions, stellar associations, and open clusters are fundamental stellar systems where predictions from star-formation theories can be robustly contrasted with observations. Aims: We aim to provide the astrophysical community with a free and open-source code to infer the phase-space (i.e. positions and velocities) parameters of stellar systems with $\\lesssim$1000 stars based on \\textit{Gaia} astrometry and possibly observed radial velocities. Methods: We upgrade an existing Bayesian hierarchical model and extend it to model 3D (positions) and 6D (positions and velocities) stellar coordinates and system parameters with a flexible variety of statistical models, including a linear velocity field. This velocity field allows for the inference of internal kinematics, including expansion, contraction, and rotation. Results: We extensively validated our statistical models using realistic simulations that mimic the properties of the \\textit{Gaia} Data Release 3. We applied \\textit{Kalkayotl} to $\\beta$-Pictoris, the Hyades, and Praesepe, recovering parameter values compatible with those from the literature. In particular, we found an expansion age of $19.1\\pm1.0$ Myr for $\\beta$-Pictoris and rotational signal of $32\\!\\pm\\!11\\,\\rm{m\\,s^{-1}\\,pc^{-1}}$ for the Hyades and that Praesepe's rotation reported in the literature comes from its periphery. Conclusions: The robust and flexible Bayesian hierarchical model that we make publicly available here represents a step forward in the statistical modelling of stellar systems. The products it delivers, such as expansion, contraction, rotation, and velocity dispersions, can be directly contrasted with predictions from star-formation theories.","url_abs":"https://arxiv.org/abs/2411.16012v1","url_pdf":"https://arxiv.org/pdf/2411.16012v1.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":"kalkayotl-2-0-bayesian-phase-space-modelling","repo_url":"https://github.com/olivares-j/Kalkayotl","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"jax","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}