{"paper":{"title":"A Neural Network Model for the Cosmic Dispersion Measure in the CAMELS Simulations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.GA"],"primary_cat":"astro-ph.CO","authors_text":"2)((1) Kavli IPMU, (2) CD3, IPMU), Khee-Gan Lee (1, Qi Guo (1)","submitted_at":"2025-01-28T05:13:57Z","abstract_excerpt":"The probability distribution, $p(\\mathrm{DM})$ of cosmic dispersion measures (DM) measured in fast radio bursts (FRBs) encodes information about both cosmology and galaxy feedback. In this work, we study the effect of feedback parameters in the $p(\\mathrm{DM})$ calculated from the full Latin Hypercube of parameters sampled by the CAMELS hydrodynamical simulation suite, building a neural network (NN) model that performs well in emulating the effect of feedback on $p(\\mathrm{DM})$ at arbitrary redshifts at $z\\leq1$. Using this NN model, we further study the parameter $F\\equiv \\sigma_{\\rm DM} \\, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.16709","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/2501.16709/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"}