{"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/model-independent-vs-model-dependent","title":"Model-independent versus model-dependent interpretation of the SDSS-III BOSS power spectrum: Bridging the divide","arxiv_id":"2106.11931","date":"2021-06-22","proceeding":null,"authors":["Samuel Brieden","Héctor Gil-Marín","Licia Verde"],"abstract":"The traditional clustering analyses of galaxy redshift surveys compress the clustering data into a set of late-time physical variables in a model-independent way. This approach has recently been extended by an additional shape variable encoding early-time physics information. We apply this new technique, ShapeFit, to SDSS-III BOSS data and show that it matches the constraining power of alternative, model-dependent approaches, which directly constrain the model's parameters adopting a cosmological model ab-initio. ShapeFit is $\\sim30$ times faster, model-independent, naturally splits early- and late-time variables, and enables a better control of observational systematics.","url_abs":"https://arxiv.org/abs/2106.11931v2","url_pdf":"https://arxiv.org/pdf/2106.11931v2.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":"model-independent-vs-model-dependent","repo_url":"https://github.com/samuelbrieden/shapefit_montepython_code","is_official":1,"mentioned_in_paper":0,"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}