{"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/neidspecmatch-stellar-parameter-estimation","title":"NEIDSpecMatch: stellar parameter estimation with NEID spectra using an empirical library","arxiv_id":"2503.16729","date":"2025-03-20","proceeding":null,"authors":["Te Han","Paul Robertson","Caleb I. Cañas","Gudmundur Stefansson","Shubham Kanodia","Joe P. Ninan","Jaime A. Alvarado-Montes","Chad F. Bender","Jiayin Dong","Rachel Fernandes","Arvind F. Gupta","Samuel Halverson","Daniel M. Krolikowski","Andrea S. J. Lin","Suvrath Mahadevan","Leonardo A. Paredes","Arpita Roy","Christian Schwab","Ryan C. Terrien"],"abstract":"We introduce NEIDSpecMatch, a tool developed to extract stellar parameters from spectra obtained with the NEID spectrograph. NEIDSpecMatch is based on SpecMatch-Emp and HPFSpecMatch, which estimate stellar parameters by comparing the observed spectrum to well-characterized library spectra. This approach has proven effective for M dwarfs. Utilizing a library of 78 stellar spectra covering effective temperatures from $3000-6000$ K, NEIDSpecMatch derives key parameters, including effective temperature, metallicity, surface gravity, and projected rotational velocity. Cross-validation shows median uncertainties of $\\sigma_{T_{\\mathrm{eff}}} = 115\\,\\mathrm{K}$, $\\sigma_{[\\mathrm{Fe/H}]} = 0.143$, and $\\sigma_{\\log g} = 0.073$ across 49 orders. We showcase its application by fitting the spectrum of an M-dwarf and discuss its utility across a wide range of spectra observed with NEID. NEIDSpecMatch is pip-installable.","url_abs":"https://arxiv.org/abs/2503.16729v1","url_pdf":"https://arxiv.org/pdf/2503.16729v1.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":"neidspecmatch-stellar-parameter-estimation","repo_url":"https://github.com/TeHanHunter/neidspecmatch","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"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}