{"paper":{"title":"Neural network-based prediction of particle-induced fission cross sections for r-process nucleosynthesis trained with dynamical reaction models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"nucl-th","authors_text":"A. Gra\\~na-Gonz\\'alez, G. Garc\\'ia-Jim\\'enez, H. Alvarez-Pol, J.L. Rodr\\'iguez-S\\'anchez, M. Feijoo-Font\\'an","submitted_at":"2025-02-24T22:46:29Z","abstract_excerpt":"Large-scale computations of fission properties play a crucial role in nuclear reaction network calculations simulating rapid neutron-capture process (r-process) nucleosynthesis. Due to the large number of fissioning nuclei contributing to the r-process, a description of particle-induced fission reactions is computationally challenging. In this work, we use theoretical calculations based on the INCL+ABLA models to train neural networks (NN). The results for the prediction of proton-induced spallation reactions, in particular fission, utilizing a large variety of NN models across the hyper-param"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.17700","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/2502.17700/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"}