{"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/growth-rate-measurement-with-type-ia","title":"Growth-rate measurement with type-Ia supernovae using ZTF survey simulations","arxiv_id":"2303.01198","date":"2023-03-02","proceeding":null,"authors":["Bastien Carreres","Julian E. Bautista","Fabrice Feinstein","Dominique Fouchez","Benjamin Racine","Mathew Smith","Mellissa Amenouche","Marie Aubert","Suhail Dhawan","Madeleine Ginolin","Ariel Goobar","Philippe Gris","Leander Lacroix","Eric Nuss","Nicolas Regnault","Mickael Rigault","Estelle Robert","Philippe Rosnet","Kelian Sommer","Richard Dekany","Steven L. Groom","Niharika Sravan","Frank J. Masci","Josiah Purdum"],"abstract":"Measurements of the growth rate of structures at $z < 0.1$ with peculiar velocity surveys have the potential of testing the validity of general relativity on cosmic scales. In this work, we present growth-rate measurements from realistic simulated sets of type-Ia supernovae (SNe Ia) from the Zwicky Transient Facility (ZTF). We describe our simulation methodology, the light-curve fitting and peculiar velocity estimation. Using the maximum likelihood method, we derive constraints on $f\\sigma_8$ using only ZTF SN Ia peculiar velocities. We carefully tested the method and we quantified biases due to selection effects (photometric detection, spectroscopic follow-up for typing) on several independent realizations. We simulated the equivalent of 6 years of ZTF data, and considering an unbiased spectroscopically typed sample at $z < 0.06$, we obtained unbiased estimates of $f\\sigma_8$ with an average uncertainty of 19% precision. We also investigated the information gain in applying bias correction methods. Our results validate our framework which can be used on real ZTF data.","url_abs":"https://arxiv.org/abs/2303.01198v2","url_pdf":"https://arxiv.org/pdf/2303.01198v2.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":"growth-rate-measurement-with-type-ia","repo_url":"https://github.com/corentinravoux/flip","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"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}