{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:BJEGYRQSDLILXX5FN3Y4HJIDR4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7b23fd70fc5c91ae3d46782889b7b4388ca579cda2ba0baee933fef336deff5a","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CE","submitted_at":"2022-12-17T20:01:57Z","title_canon_sha256":"e4355ccc97277aba771da9d8434755dbb8c1b4bfa52b8f45cd7b2763b2a6d23b"},"schema_version":"1.0","source":{"id":"2212.08939","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.08939","created_at":"2026-07-05T05:26:15Z"},{"alias_kind":"arxiv_version","alias_value":"2212.08939v1","created_at":"2026-07-05T05:26:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.08939","created_at":"2026-07-05T05:26:15Z"},{"alias_kind":"pith_short_12","alias_value":"BJEGYRQSDLIL","created_at":"2026-07-05T05:26:15Z"},{"alias_kind":"pith_short_16","alias_value":"BJEGYRQSDLILXX5F","created_at":"2026-07-05T05:26:15Z"},{"alias_kind":"pith_short_8","alias_value":"BJEGYRQS","created_at":"2026-07-05T05:26:15Z"}],"graph_snapshots":[{"event_id":"sha256:c6524fad8c2970f61a9eb876fca4eacd0fb8d09696d30fb7ff2e869a2a3d8ea0","target":"graph","created_at":"2026-07-05T05:26:15Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2212.08939/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Inspired by our previous work on mitigating the Kolmogorov barrier using a quadratic approximation manifold, we propose in this paper a computationally tractable approach for combining a projection-based reduced-order model (PROM) and an artificial neural network (ANN) for mitigating the Kolmogorov barrier to reducibility of convection-dominated flow problems. The main objective the PROM-ANN concept that we propose is to reduce the dimensionality of the online approximation of the solution beyond what is possible using affine and quadratic approximation manifolds. In contrast to previous appro","authors_text":"Charbel Farhat, Joshua L Barnett, Yvon Maday","cross_cats":["cs.NA","math.NA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CE","submitted_at":"2022-12-17T20:01:57Z","title":"Neural-Network-Augmented Projection-Based Model Order Reduction for Mitigating the Kolmogorov Barrier to Reducibility of CFD Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.08939","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0ce0a13d9b55472253445b44c2f66f3bb181eb09d3fdbef5a6d238dce7f57519","target":"record","created_at":"2026-07-05T05:26:15Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7b23fd70fc5c91ae3d46782889b7b4388ca579cda2ba0baee933fef336deff5a","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CE","submitted_at":"2022-12-17T20:01:57Z","title_canon_sha256":"e4355ccc97277aba771da9d8434755dbb8c1b4bfa52b8f45cd7b2763b2a6d23b"},"schema_version":"1.0","source":{"id":"2212.08939","kind":"arxiv","version":1}},"canonical_sha256":"0a486c46121ad0bbdfa56ef1c3a5038f0704ae6e545873a308204e9a17bb228e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0a486c46121ad0bbdfa56ef1c3a5038f0704ae6e545873a308204e9a17bb228e","first_computed_at":"2026-07-05T05:26:15.888159Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:26:15.888159Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"szvSPjYCLsLUSVEYmyZFCZOk4zRf4pNGxb4GIiUH7Ia+JAdPGdFXjYolcwg6WTOUBHvIJvb2fZeM9iOjnOtrDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:26:15.888574Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.08939","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ce0a13d9b55472253445b44c2f66f3bb181eb09d3fdbef5a6d238dce7f57519","sha256:c6524fad8c2970f61a9eb876fca4eacd0fb8d09696d30fb7ff2e869a2a3d8ea0"],"state_sha256":"186833d652ebfb85b4703117c5c3dd5eeb44863556070d55987e7efadf093d95"}