{"paper":{"title":"ForestFlow: predicting the Lyman-$\\alpha$ forest clustering from linear to nonlinear scales","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"A. de la Macorra, A. Font-Ribera, A. Kremin, A. Lambert, A. Mu\\~noz-Guti\\'errez, B. A. Weaver, D. Bianchi, D. Brooks, D. Kirkby, D. Sprayberry, E. Gazta\\~naga, E. Sanchez, G. Gutierrez, G. Niz, G. Rossi, G. Tarl\\'e, I. P\\'erez-R\\`afols, J. Aguilar, J. Chaves-Montero, J. E. Forero-Romero, K. Honscheid, L. Cabayol-Garcia, M. Landriau, M. Lokken, M. Manera, M. Schubnell, P. Martini, R. Kehoe, R. Miquel, S. Ahlen, S. Cole, S. Ferraro, S. Gontcho A Gontcho, T. Claybaugh","submitted_at":"2024-09-09T14:52:15Z","abstract_excerpt":"On large scales, the Lyman-$\\alpha$ forest provides insights into the expansion history of the Universe, while on small scales, it imposes strict constraints on the growth history, the nature of dark matter, and the sum of neutrino masses. This work introduces ForestFlow, a novel framework that bridges the gap between large- and small-scale analyses, which have traditionally relied on distinct modeling approaches. Using conditional normalizing flows, ForestFlow predicts the two Lyman-$\\alpha$ linear biases ($b_\\delta$ and $b_\\eta$) and six parameters describing small-scale deviations of the th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.05682","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.05682/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}