{"paper":{"title":"Flow-Based Surrogates for High-Dimensional Likelihoods in Experimental Neutrino Physics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"hep-ex","authors_text":"Adrien Blanchet, Federico S\\'anchez, Lorenzo Giannessi, Mathias El Baz","submitted_at":"2026-07-03T16:42:36Z","abstract_excerpt":"Precision long-baseline neutrino experiments use near-detector data to constrain systematic uncertainties on the unoscillated neutrino flux, a prerequisite for accurate oscillation parameter measurements at the far detector. When the constrained likelihood is high-dimensional and non-Gaussian, this procedure demands advanced statistical treatment. Here we show that normalizing flows provide faithful and portable likelihood models for this problem. Leveraging an initial Gaussian approximation of the likelihood, we train a hybrid architecture combining coupling transformations and autoregressive"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.03477","kind":"arxiv","version":1},"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/2607.03477/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"}