{"paper":{"title":"Constraining Black Hole Parameters in Non-Commutative Geometry using Machine Learning","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["hep-th"],"primary_cat":"gr-qc","authors_text":"Maryem Jemri","submitted_at":"2026-05-19T18:39:03Z","abstract_excerpt":"Motivated by string theory, we constrain non-commutative black hole parameters through shadow behaviors using machine learning techniques combined by CUDA computations. To do so, we first investigate the structure of the event horizon of non-commutative black holes in the presence of string clouds and dark energy sectors by exploiting CUDA-based methods. We numerically approach the shadow properties and the energy emission rate of rotating and charged black holes in non-commutative geometry via such high-performance parallel computings. To bridge these findings with observational data, we impl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.22862","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/2605.22862/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"}