{"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/gallifray-a-geometric-modeling-and-parameter","title":"GALLIFRAY -- A geometric modeling and parameter estimation framework for black hole images using bayesian techniques","arxiv_id":"2212.06827","date":"2022-12-13","proceeding":null,"authors":["Saurabh","Sourabh Nampalliwar"],"abstract":"Recent observations of the galactic centers of M87 and the Milky Way with the Event Horizon Telescope have ushered in a new era of black hole based tests of fundamental physics using very long baseline interferometry (VLBI). Being a nascent field, there are several different modeling and analysis approaches in vogue (e.g., geometric and physical models, visibility and closure amplitudes, agnostic and multimessenger priors). We present \\texttt{GALLIFRAY}, an open-source Python-based framework for estimation/extraction of parameters using VLBI data. It is developed with modularity, efficiency, and adaptability as the primary objectives. This article outlines the design and usage of \\texttt{GALLIFRAY}. As an illustration, we fit a geometric and a physical model to simulated datasets using markov chain monte carlo sampling and find good convergence of the posterior distribution. We conclude with an outline of further enhancements currently in development.","url_abs":"https://arxiv.org/abs/2212.06827v2","url_pdf":"https://arxiv.org/pdf/2212.06827v2.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":"gallifray-a-geometric-modeling-and-parameter","repo_url":"https://github.com/Relativist1/Gallifray","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","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}