{"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/flows-for-the-masses-a-multi-fluid-non-linear","title":"Flows For The Masses: A multi-fluid non-linear perturbation theory for massive neutrinos","arxiv_id":"2210.16020","date":"2022-10-28","proceeding":null,"authors":["Joe Zhiyu Chen","Amol Upadhye","Yvonne Y. Y. Wong"],"abstract":"Velocity dispersion of the massive neutrinos presents a daunting challenge for non-linear cosmological perturbation theory. We consider the neutrino population as a collection of non-linear fluids, each with uniform initial momentum, through an extension of the Time Renormalization Group perturbation theory. Employing recently-developed Fast Fourier Transform techniques, we accelerate our non-linear perturbation theory by more than two orders of magnitude, making it quick enough for practical use. After verifying that the neutrino mode-coupling integrals and power spectra converge, we show that our perturbation theory agrees with N-body neutrino simulations to within 10% for neutrino fractions $\\Omega_{\\nu,0} h^2 \\leq 0.005$ up to wave numbers of k = 1 h/Mpc, an accuracy consistent with 2.5% errors in the neutrino mass determination. Non-linear growth represents a >10% correction to the neutrino power spectrum even for density fractions as low as $\\Omega_{\\nu,0} h^2 = 0.001$, demonstrating the limits of linear theory for accurate neutrino power spectrum predictions. Our code FlowsForTheMasses is avaliable online at github.com/upadhye/FlowsForTheMasses .","url_abs":"https://arxiv.org/abs/2210.16020v2","url_pdf":"https://arxiv.org/pdf/2210.16020v2.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":"flows-for-the-masses-a-multi-fluid-non-linear","repo_url":"https://github.com/upadhye/flowsforthemasses","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"flows-for-the-masses-a-multi-fluid-non-linear","repo_url":"https://github.com/upadhye/flowsforthemassesii","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}