{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:ECU6QNLTLSNO2IYPTUZYZTPI6C","short_pith_number":"pith:ECU6QNLT","schema_version":"1.0","canonical_sha256":"20a9e835735c9aed230f9d338ccde8f08871a450f458c9402ae6857c79616cf1","source":{"kind":"arxiv","id":"1711.01728","version":3},"attestation_state":"computed","paper":{"title":"PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE"],"primary_cat":"math.OC","authors_text":"Carleton Coffrin, Kaarthik Sundar, Miles Lubin, Russell Bent, Yeesian Ng","submitted_at":"2017-11-06T04:58:07Z","abstract_excerpt":"In recent years, the power system research community has seen an explosion of novel methods for formulating and solving power network optimization problems. These emerging methods range from new power flow approximations, which go beyond the traditional DC power flow by capturing reactive power, to convex relaxations, which provide solution quality and runtime performance guarantees. Unfortunately, the sophistication of these emerging methods often presents a significant barrier to evaluating them on a wide variety of power system optimization applications. To address this issue, this work pro"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1711.01728","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-11-06T04:58:07Z","cross_cats_sorted":["cs.CE"],"title_canon_sha256":"33100105288c33b4ec1c175dcb35113361600c4d008095e90d309cb79b3fd00b","abstract_canon_sha256":"deb3639b70a262e0d5d6248dd5c158064722f345b317bc8adcbf6175de11a4a9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:21:21.740118Z","signature_b64":"qunZDCTDJlL8gilDwMNDeEF7yFqABRsvufdrAxEVXUZOUSCnJa5+z4nTY9j5xJhy9CmrZHoAHwGkFLEeSqZ2Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20a9e835735c9aed230f9d338ccde8f08871a450f458c9402ae6857c79616cf1","last_reissued_at":"2026-05-18T00:21:21.739430Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:21:21.739430Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE"],"primary_cat":"math.OC","authors_text":"Carleton Coffrin, Kaarthik Sundar, Miles Lubin, Russell Bent, Yeesian Ng","submitted_at":"2017-11-06T04:58:07Z","abstract_excerpt":"In recent years, the power system research community has seen an explosion of novel methods for formulating and solving power network optimization problems. These emerging methods range from new power flow approximations, which go beyond the traditional DC power flow by capturing reactive power, to convex relaxations, which provide solution quality and runtime performance guarantees. Unfortunately, the sophistication of these emerging methods often presents a significant barrier to evaluating them on a wide variety of power system optimization applications. To address this issue, this work pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.01728","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1711.01728","created_at":"2026-05-18T00:21:21.739535+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.01728v3","created_at":"2026-05-18T00:21:21.739535+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.01728","created_at":"2026-05-18T00:21:21.739535+00:00"},{"alias_kind":"pith_short_12","alias_value":"ECU6QNLTLSNO","created_at":"2026-05-18T12:31:12.930513+00:00"},{"alias_kind":"pith_short_16","alias_value":"ECU6QNLTLSNO2IYP","created_at":"2026-05-18T12:31:12.930513+00:00"},{"alias_kind":"pith_short_8","alias_value":"ECU6QNLT","created_at":"2026-05-18T12:31:12.930513+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C","json":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C.json","graph_json":"https://pith.science/api/pith-number/ECU6QNLTLSNO2IYPTUZYZTPI6C/graph.json","events_json":"https://pith.science/api/pith-number/ECU6QNLTLSNO2IYPTUZYZTPI6C/events.json","paper":"https://pith.science/paper/ECU6QNLT"},"agent_actions":{"view_html":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C","download_json":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C.json","view_paper":"https://pith.science/paper/ECU6QNLT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.01728&json=true","fetch_graph":"https://pith.science/api/pith-number/ECU6QNLTLSNO2IYPTUZYZTPI6C/graph.json","fetch_events":"https://pith.science/api/pith-number/ECU6QNLTLSNO2IYPTUZYZTPI6C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C/action/storage_attestation","attest_author":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C/action/author_attestation","sign_citation":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C/action/citation_signature","submit_replication":"https://pith.science/pith/ECU6QNLTLSNO2IYPTUZYZTPI6C/action/replication_record"}},"created_at":"2026-05-18T00:21:21.739535+00:00","updated_at":"2026-05-18T00:21:21.739535+00:00"}