{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DVEKH3HK72TPD3TGNAWSK4PTKB","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":"d2965726b33b9ad8d3a2388fb75403578ce05707475198fc25d0b25308903570","cross_cats_sorted":["cs.NA","physics.comp-ph"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"math.NA","submitted_at":"2026-04-09T16:49:55Z","title_canon_sha256":"c6156e3b3572c1373c9702aa0d0968f355301b7bc8194517c2970de6079def09"},"schema_version":"1.0","source":{"id":"2604.08453","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.08453","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"arxiv_version","alias_value":"2604.08453v2","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.08453","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_12","alias_value":"DVEKH3HK72TP","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_16","alias_value":"DVEKH3HK72TPD3TG","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_8","alias_value":"DVEKH3HK","created_at":"2026-05-20T00:02:11Z"}],"graph_snapshots":[{"event_id":"sha256:0cb05e81708b3efe3a13844de65d9734e3059a79e4d996dc68f9b4cef769a46f","target":"graph","created_at":"2026-05-20T00:02:11Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"We introduce two ansatz-based hard-constrained PINN formulations for interface problems that embed the interface physics into the solution representation and thereby decouple interface enforcement from PDE residual minimization."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That the windowing construction remains stable for general interface geometries and that the discrete buffer correction points can be chosen without introducing new fitting parameters that affect accuracy."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"Hard-constrained PINN formulations via windowing and buffer approaches enforce interface conditions by design and outperform soft-constrained baselines on 1D and 2D elliptic interface problems."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Hard-constrained PINN formulations embed interface continuity and flux conditions directly into the neural network solution representation."}],"snapshot_sha256":"bf6c4ac925f166c902ea89ad9b28681e7472aa6068d71d8645619cf37d2718a7"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2604.08453/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Physics-informed neural networks (PINNs) have emerged as a flexible framework for solving partial differential equations, but their performance on interface problems remains challenging because continuity and flux conditions are typically imposed through soft penalty terms. The standard soft-constraint formulation leads to imperfect interface enforcement and degraded accuracy near interfaces. We introduce two ansatz-based hard-constrained PINN formulations for interface problems that embed the interface physics into the solution representation and thereby decouple interface enforcement from PD","authors_text":"Michael S. Penwarden, Pratanu Roy, Seung Whan Chung, Stephen T. Castonguay, Sumanta Roy, Yucheng Fu","cross_cats":["cs.NA","physics.comp-ph"],"headline":"Hard-constrained PINN formulations embed interface continuity and flux conditions directly into the neural network solution representation.","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"math.NA","submitted_at":"2026-04-09T16:49:55Z","title":"Hard-constrained Physics-informed Neural Networks for Interface Problems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.08453","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-10T17:04:06.400202Z","id":"665b6f84-fd08-4a9e-bf75-25015d7e1ba2","model_set":{"reader":"grok-4.3"},"one_line_summary":"Hard-constrained PINN formulations via windowing and buffer approaches enforce interface conditions by design and outperform soft-constrained baselines on 1D and 2D elliptic interface problems.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Hard-constrained PINN formulations embed interface continuity and flux conditions directly into the neural network solution representation.","strongest_claim":"We introduce two ansatz-based hard-constrained PINN formulations for interface problems that embed the interface physics into the solution representation and thereby decouple interface enforcement from PDE residual minimization.","weakest_assumption":"That the windowing construction remains stable for general interface geometries and that the discrete buffer correction points can be chosen without introducing new fitting parameters that affect accuracy."}},"verdict_id":"665b6f84-fd08-4a9e-bf75-25015d7e1ba2"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:69400e491e742684352d2c7bc15e0d20768a6f32c0834b254095f7714e846e7a","target":"record","created_at":"2026-05-20T00:02:11Z","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":"d2965726b33b9ad8d3a2388fb75403578ce05707475198fc25d0b25308903570","cross_cats_sorted":["cs.NA","physics.comp-ph"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"math.NA","submitted_at":"2026-04-09T16:49:55Z","title_canon_sha256":"c6156e3b3572c1373c9702aa0d0968f355301b7bc8194517c2970de6079def09"},"schema_version":"1.0","source":{"id":"2604.08453","kind":"arxiv","version":2}},"canonical_sha256":"1d48a3eceafea6f1ee66682d2571f3507bbbca90f62b5b76cf49166b94a3d3dc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1d48a3eceafea6f1ee66682d2571f3507bbbca90f62b5b76cf49166b94a3d3dc","first_computed_at":"2026-05-20T00:02:11.353662Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:02:11.353662Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IccyGz4EoxLOYXlN9EfabBVcqQVj9roM5WLsthjV3qkAAihWFzkTA5laOYceyFppIeg5kWOB2jvp3GYT8n1qBw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:02:11.354438Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.08453","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:69400e491e742684352d2c7bc15e0d20768a6f32c0834b254095f7714e846e7a","sha256:0cb05e81708b3efe3a13844de65d9734e3059a79e4d996dc68f9b4cef769a46f"],"state_sha256":"d8bd978db0171d64cd67969f134a5a8b12b7ebcf6defad9b29c52e6a8d340e47"}