{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:DFOOIE2ZHRRRPOITKTARGQLBHG","short_pith_number":"pith:DFOOIE2Z","canonical_record":{"source":{"id":"2505.22825","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-28T20:10:04Z","cross_cats_sorted":["cs.AI","cs.SY","eess.SY","math.OC"],"title_canon_sha256":"b53e6f2a8083f81ea436dd31408136037c9b7d68053924c635c3372d8113054a","abstract_canon_sha256":"b64bcaf4c30be863fb2d6ccc27c988d8fa7bd43dc3c4d04cc1595c019ea2eac1"},"schema_version":"1.0"},"canonical_sha256":"195ce413593c6317b91354c11341613985ca4b4d59e15f7d5e771166411a9a89","source":{"kind":"arxiv","id":"2505.22825","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.22825","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"arxiv_version","alias_value":"2505.22825v1","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.22825","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"pith_short_12","alias_value":"DFOOIE2ZHRRR","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"pith_short_16","alias_value":"DFOOIE2ZHRRRPOIT","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"pith_short_8","alias_value":"DFOOIE2Z","created_at":"2026-07-05T11:11:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:DFOOIE2ZHRRRPOITKTARGQLBHG","target":"record","payload":{"canonical_record":{"source":{"id":"2505.22825","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-28T20:10:04Z","cross_cats_sorted":["cs.AI","cs.SY","eess.SY","math.OC"],"title_canon_sha256":"b53e6f2a8083f81ea436dd31408136037c9b7d68053924c635c3372d8113054a","abstract_canon_sha256":"b64bcaf4c30be863fb2d6ccc27c988d8fa7bd43dc3c4d04cc1595c019ea2eac1"},"schema_version":"1.0"},"canonical_sha256":"195ce413593c6317b91354c11341613985ca4b4d59e15f7d5e771166411a9a89","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:11:50.419380Z","signature_b64":"nOwcamtHtyE4QUGbABnNEjYiHLxHrD677UTyyXkG4FiRQGBj6BLxytZSb+XhwaEQUn+wJyijT/R+D2IfG0ToAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"195ce413593c6317b91354c11341613985ca4b4d59e15f7d5e771166411a9a89","last_reissued_at":"2026-07-05T11:11:50.418875Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:11:50.418875Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.22825","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:11:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c+dydYR8ZMtgumuHbVoWZUM4Wkfmmq92cNOjXwz8OzrkKc43rUpfk8WBIVi/0kdJz5BRQmzzz+8bKM1t0uCaCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:20:56.271494Z"},"content_sha256":"ecb030d323a368ad26a1a6848b6f1badf4162cba9a98d0a57236597ed2d64d14","schema_version":"1.0","event_id":"sha256:ecb030d323a368ad26a1a6848b6f1badf4162cba9a98d0a57236597ed2d64d14"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:DFOOIE2ZHRRRPOITKTARGQLBHG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.SY","eess.SY","math.OC"],"primary_cat":"cs.LG","authors_text":"Mathieu Tanneau, Michael Klamkin, Pascal Van Hentenryck","submitted_at":"2025-05-28T20:10:04Z","abstract_excerpt":"Machine Learning (ML) techniques for Optimal Power Flow (OPF) problems have recently garnered significant attention, reflecting a broader trend of leveraging ML to approximate and/or accelerate the resolution of complex optimization problems. These developments are necessitated by the increased volatility and scale in energy production for modern and future grids. However, progress in ML for OPF is hindered by the lack of standardized datasets and evaluation metrics, from generating and solving OPF instances, to training and benchmarking machine learning models. To address this challenge, this"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.22825","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/2505.22825/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:11:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5KA2GNsygaHM804kupMI+zSXPLAFaj58Q2nZ+KJ0WffsVjBcTQlTcOca+ad1q4HS2rPN+hEyDrOOYAOYqBNHAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:20:56.272088Z"},"content_sha256":"2b78443b6c8a02e7e77bf5567f6fa75a02935c50366de3aa0c2ad0f84da083de","schema_version":"1.0","event_id":"sha256:2b78443b6c8a02e7e77bf5567f6fa75a02935c50366de3aa0c2ad0f84da083de"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DFOOIE2ZHRRRPOITKTARGQLBHG/bundle.json","state_url":"https://pith.science/pith/DFOOIE2ZHRRRPOITKTARGQLBHG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DFOOIE2ZHRRRPOITKTARGQLBHG/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T14:20:56Z","links":{"resolver":"https://pith.science/pith/DFOOIE2ZHRRRPOITKTARGQLBHG","bundle":"https://pith.science/pith/DFOOIE2ZHRRRPOITKTARGQLBHG/bundle.json","state":"https://pith.science/pith/DFOOIE2ZHRRRPOITKTARGQLBHG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DFOOIE2ZHRRRPOITKTARGQLBHG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DFOOIE2ZHRRRPOITKTARGQLBHG","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":"b64bcaf4c30be863fb2d6ccc27c988d8fa7bd43dc3c4d04cc1595c019ea2eac1","cross_cats_sorted":["cs.AI","cs.SY","eess.SY","math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-28T20:10:04Z","title_canon_sha256":"b53e6f2a8083f81ea436dd31408136037c9b7d68053924c635c3372d8113054a"},"schema_version":"1.0","source":{"id":"2505.22825","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.22825","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"arxiv_version","alias_value":"2505.22825v1","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.22825","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"pith_short_12","alias_value":"DFOOIE2ZHRRR","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"pith_short_16","alias_value":"DFOOIE2ZHRRRPOIT","created_at":"2026-07-05T11:11:50Z"},{"alias_kind":"pith_short_8","alias_value":"DFOOIE2Z","created_at":"2026-07-05T11:11:50Z"}],"graph_snapshots":[{"event_id":"sha256:2b78443b6c8a02e7e77bf5567f6fa75a02935c50366de3aa0c2ad0f84da083de","target":"graph","created_at":"2026-07-05T11:11:50Z","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/2505.22825/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine Learning (ML) techniques for Optimal Power Flow (OPF) problems have recently garnered significant attention, reflecting a broader trend of leveraging ML to approximate and/or accelerate the resolution of complex optimization problems. These developments are necessitated by the increased volatility and scale in energy production for modern and future grids. However, progress in ML for OPF is hindered by the lack of standardized datasets and evaluation metrics, from generating and solving OPF instances, to training and benchmarking machine learning models. To address this challenge, this","authors_text":"Mathieu Tanneau, Michael Klamkin, Pascal Van Hentenryck","cross_cats":["cs.AI","cs.SY","eess.SY","math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-28T20:10:04Z","title":"PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.22825","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:ecb030d323a368ad26a1a6848b6f1badf4162cba9a98d0a57236597ed2d64d14","target":"record","created_at":"2026-07-05T11:11:50Z","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":"b64bcaf4c30be863fb2d6ccc27c988d8fa7bd43dc3c4d04cc1595c019ea2eac1","cross_cats_sorted":["cs.AI","cs.SY","eess.SY","math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-28T20:10:04Z","title_canon_sha256":"b53e6f2a8083f81ea436dd31408136037c9b7d68053924c635c3372d8113054a"},"schema_version":"1.0","source":{"id":"2505.22825","kind":"arxiv","version":1}},"canonical_sha256":"195ce413593c6317b91354c11341613985ca4b4d59e15f7d5e771166411a9a89","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"195ce413593c6317b91354c11341613985ca4b4d59e15f7d5e771166411a9a89","first_computed_at":"2026-07-05T11:11:50.418875Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:11:50.418875Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nOwcamtHtyE4QUGbABnNEjYiHLxHrD677UTyyXkG4FiRQGBj6BLxytZSb+XhwaEQUn+wJyijT/R+D2IfG0ToAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:11:50.419380Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.22825","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ecb030d323a368ad26a1a6848b6f1badf4162cba9a98d0a57236597ed2d64d14","sha256:2b78443b6c8a02e7e77bf5567f6fa75a02935c50366de3aa0c2ad0f84da083de"],"state_sha256":"ce0a8fb07bd6197310050575be592324bfde1d81a55d5db46fed05d12330f98a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RUEfqnReEt1LdP2y1uhQqgnXIfix3kx5WbaQQ+9xeeUDvdHsMD3FW5EWtcbFDNlJKjfk/axWp0UkYTcjvoSnBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T14:20:56.297808Z","bundle_sha256":"17090291a65a387e5db69d18f5e89983df442b6311ad5c79c373e5683a2dc2bb"}}