{"paper":{"title":"The role of the likelihood for elastic scattering uncertainty quantification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"nucl-th","authors_text":"A. E. Lovell, C. D. Pruitt, C. Hebborn, F. M. Nunes","submitted_at":"2024-03-01T18:52:47Z","abstract_excerpt":"Background: Analyses of elastic scattering with the optical model (OMP) are widely used in nuclear reactions.\n  Purpose: Previous work compared a traditional frequentist approach and a Bayesian approach to quantify uncertainties in the OMP. In this study, we revisit this comparison and consider the role of the likelihood used in the analysis.\n  Method: We compare the Levenberg-Marquardt algorithm for $\\chi^{2}$ minimization with Markov Chain Monte Carlo sampling to obtain parameter posteriors. Following previous work, we consider how results are affected when $\\chi^{2}$/N is used for the likel"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.00753","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/2403.00753/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"}