{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:KBW6C5VRB64VYSWCUWGT43TCOF","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":"b469ba7ffbf1644c5887ad92733410fccc0183503cc54c6b8198620b1350b255","cross_cats_sorted":["cs.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2025-06-11T15:10:02Z","title_canon_sha256":"8d0c001883e75a9b0cc535499fb95bcddc64ed2392d62b52d11a932b62ca571f"},"schema_version":"1.0","source":{"id":"2506.09830","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.09830","created_at":"2026-05-26T02:05:00Z"},{"alias_kind":"arxiv_version","alias_value":"2506.09830v2","created_at":"2026-05-26T02:05:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.09830","created_at":"2026-05-26T02:05:00Z"},{"alias_kind":"pith_short_12","alias_value":"KBW6C5VRB64V","created_at":"2026-05-26T02:05:00Z"},{"alias_kind":"pith_short_16","alias_value":"KBW6C5VRB64VYSWC","created_at":"2026-05-26T02:05:00Z"},{"alias_kind":"pith_short_8","alias_value":"KBW6C5VR","created_at":"2026-05-26T02:05:00Z"}],"graph_snapshots":[{"event_id":"sha256:678a912b53eebfd9ced5d8ace41ec4470dbb209b963450b0de03394f61c65c26","target":"graph","created_at":"2026-05-26T02:05:00Z","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/2506.09830/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the present work, we introduce a data-driven approach to enhance the accuracy of non-intrusive Reduced Order Models (ROMs). In particular, we focus on ROMs built using Proper Orthogonal Decomposition (POD) in an under-resolved and marginally-resolved regime, i.e. when the number of modes employed is not enough to capture the system dynamics. We propose a method to re-introduce the contribution of neglected modes through a quadratic correction term, given by the action of a quadratic operator on the POD coefficients. Differently from the state-of-the-art methodologies, where the operator is ","authors_text":"Anna Ivagnes, Gabriele Codega, Gianluigi Rozza, Nicola Demo","cross_cats":["cs.NA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2025-06-11T15:10:02Z","title":"Machine Learning-based quadratic closures for non-intrusive Reduced Order Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.09830","kind":"arxiv","version":2},"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:db33cb8592890471b65a81c04c854a46cda0c6bfacf96ce1f0ffaa75324554e9","target":"record","created_at":"2026-05-26T02:05:00Z","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":"b469ba7ffbf1644c5887ad92733410fccc0183503cc54c6b8198620b1350b255","cross_cats_sorted":["cs.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2025-06-11T15:10:02Z","title_canon_sha256":"8d0c001883e75a9b0cc535499fb95bcddc64ed2392d62b52d11a932b62ca571f"},"schema_version":"1.0","source":{"id":"2506.09830","kind":"arxiv","version":2}},"canonical_sha256":"506de176b10fb95c4ac2a58d3e6e627179557201a7a1bfdd2be4e000dc1bf325","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"506de176b10fb95c4ac2a58d3e6e627179557201a7a1bfdd2be4e000dc1bf325","first_computed_at":"2026-05-26T02:05:00.651998Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:05:00.651998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R+yTDqNGQ05KifzSX0eAqGBZH3fs9OCQnYYYBBHliZjrjiXlFJrIYe4m7mLXwOEBYWvWXFrjqYEZ8gVjsxgTAA==","signature_status":"signed_v1","signed_at":"2026-05-26T02:05:00.652745Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.09830","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:db33cb8592890471b65a81c04c854a46cda0c6bfacf96ce1f0ffaa75324554e9","sha256:678a912b53eebfd9ced5d8ace41ec4470dbb209b963450b0de03394f61c65c26"],"state_sha256":"eb7a67d1e52c103b2a06486f434ef2b0c92719b415ae28c2d97bc934567d7f30"}