{"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/pancake-python-based-numerical-color","title":"PANCAKE: Python bAsed Numerical Color-magnitude-diagram Analysis pacKagE","arxiv_id":"2505.04534","date":"2025-05-07","proceeding":null,"authors":["Yun Zheng","Yujiao Yang","Yong-kun Zhang","Zheng Zheng","Jing Wang","Lister Staveley-Smith","Chao-Wei Tsai","Di Li","Chao Liu","Jingjing Hu","Huaxi Chen","Donghui Quan","Yinghui Zheng","Hangyuan Li"],"abstract":"Stellar populations serve as a fossil record of galaxy formation and evolution, providing crucial information about the history of star formation and galaxy evolution. The color-magnitude diagram (CMD) stands out as the most accurate tool currently available for inferring the star formation histories (SFHs) of nearby galaxies with stellar-resolved multiband data. The launch of new space telescopes, including JWST, EUCLID, and the upcoming CSST and Roman, will significantly increase the number of stellar-resolved galaxies over the next decade. A user-friendly and customizable CMD fitting package would be valuable for galaxy evolution studies with these data. We develop an open-source Python-based package named \\textsc{pancake}, which is fast and accurate in determining SFHs and stellar population parameters in nearby galaxies. We have validated our method via a series of comprehensive tests. First, \\textsc{pancake} performs well on mock data, meanwhile the random and systematic uncertainties are quantified. Second, \\textsc{pancake} performs well on observational data containing a star cluster and 38 dwarf galaxies (50 fields). Third, the star formation rate (SFR) from \\textsc{pancake} is consistent with the SFR from FUV photometry. To ensure compatibility and accuracy, we have included isochrone libraries generated using PARSEC for most of the optical and near-infrared filters used in space telescopes such as HST, JWST, and the upcoming CSST.","url_abs":"https://arxiv.org/abs/2505.04534v1","url_pdf":"https://arxiv.org/pdf/2505.04534v1.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":"pancake-python-based-numerical-color","repo_url":"https://github.com/yunzheng168/pancake","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","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}