{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:YEMOMCBTIUDSEOVERI7BP3GSNI","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":"3439c56adfb72d77d4b1ad42910e61516b8b497b88b828ff2e25f9f40ffcdfc4","cross_cats_sorted":["cs.SY","eess.SY","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-31T18:25:03Z","title_canon_sha256":"f5903b0645508db449b6734c04881ab5f959b11eb788351d44eb466ae6e4d878"},"schema_version":"1.0","source":{"id":"2304.00062","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.00062","created_at":"2026-07-05T05:56:58Z"},{"alias_kind":"arxiv_version","alias_value":"2304.00062v1","created_at":"2026-07-05T05:56:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.00062","created_at":"2026-07-05T05:56:58Z"},{"alias_kind":"pith_short_12","alias_value":"YEMOMCBTIUDS","created_at":"2026-07-05T05:56:58Z"},{"alias_kind":"pith_short_16","alias_value":"YEMOMCBTIUDSEOVE","created_at":"2026-07-05T05:56:58Z"},{"alias_kind":"pith_short_8","alias_value":"YEMOMCBT","created_at":"2026-07-05T05:56:58Z"}],"graph_snapshots":[{"event_id":"sha256:3ab7a78c346cab56ad1f985626a21b5feca0a1f327310bdadf5fd7be7fee57b6","target":"graph","created_at":"2026-07-05T05:56:58Z","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/2304.00062/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper addresses the challenge of efficiently solving the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Aware Active Set learning OPF (PIMA-AS-OPF), leverages physical constraints and market properties to ensure physical and economic feasibility of market-clearing outcomes. Specifically, PIMA-AS-OPF employs the active set learning technique and expands its capabilities to account for curtailment in load or renewable power generation, which is a common challenge in real-world power systems. The core of PIMA-AS-OPF is a full","authors_text":"Daniel Bienstock, Laurent Pagnier, Michael Chertkov, Robert Ferrando, Robert Mieth, Yury Dvorkin, Zhirui Liang","cross_cats":["cs.SY","eess.SY","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-31T18:25:03Z","title":"A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.00062","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:acc099b22dcacfd24c3e6dbf8f0ab737df1985e540e5ee35a77dd4e4b09c2c55","target":"record","created_at":"2026-07-05T05:56:58Z","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":"3439c56adfb72d77d4b1ad42910e61516b8b497b88b828ff2e25f9f40ffcdfc4","cross_cats_sorted":["cs.SY","eess.SY","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-31T18:25:03Z","title_canon_sha256":"f5903b0645508db449b6734c04881ab5f959b11eb788351d44eb466ae6e4d878"},"schema_version":"1.0","source":{"id":"2304.00062","kind":"arxiv","version":1}},"canonical_sha256":"c118e608334507223aa48a3e17ecd26a016bc2f44cbe8093cab70e7084656fdf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c118e608334507223aa48a3e17ecd26a016bc2f44cbe8093cab70e7084656fdf","first_computed_at":"2026-07-05T05:56:58.238657Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:56:58.238657Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yQ4Xe96Kd1GZ7ffR3KPXICwjKmpJwEhWcuAKhWXCbuSNe0X8czWLZa+Kd5CGiscp7yj2wdj94ZTgnLPSKtMnAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:56:58.239095Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.00062","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:acc099b22dcacfd24c3e6dbf8f0ab737df1985e540e5ee35a77dd4e4b09c2c55","sha256:3ab7a78c346cab56ad1f985626a21b5feca0a1f327310bdadf5fd7be7fee57b6"],"state_sha256":"31885c7309c61971db3986ecab55d91a8b886e4c70dcbd2cb8d417b96e7f4559"}