{"paper":{"title":"Kilonova modelling and parameter inference: Understanding uncertainties and evaluating compatibility between observations and models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM"],"primary_cat":"astro-ph.HE","authors_text":"(2) STAR institute Universit\\'e de Li\\`ege, 3), (3) Observatoire de la C\\^ote d'Azur, (4) Nikhef, 5) ((1) Universit\\'e Paris-Saclay, (5) Institute for Gravitational, CNRS/IN2P3, IJCLab, Marion Pillas (2), Patrice Hello (1), Peter T. H. Pang (4, Sarah Antier (1, Subatomic Physics (GRASP), Thomas Hussenot-Desenonges (1), Utrecht University)","submitted_at":"2025-05-27T16:20:00Z","abstract_excerpt":"In the study of optical transients, parameter inference is the process of extracting physical information, i.e. constraints on the source's characteristics, by comparing the observed lightcurves to the predictions of different models and finding the model and parameter combination that make the closest match. In the developing field of the study of kilonovae (KNe), systematic uncertainties in modelling are still very large, and many models struggle to fit satisfactorily the whole multi-wavelength dataset of the AT2017gfo kilonova, associated to the Binary Neutron Star (BNS) merger GW170817. In"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.21392","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/2505.21392/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"}