{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:2A5FIH3IDK5B4HYJR6OMUSHAOW","short_pith_number":"pith:2A5FIH3I","schema_version":"1.0","canonical_sha256":"d03a541f681aba1e1f098f9cca48e07597ef2caa9b099d10ef557524441b0380","source":{"kind":"arxiv","id":"1605.08336","version":1},"attestation_state":"computed","paper":{"title":"Distributed Gauss-Newton Method for AC State Estimation: A Belief Propagation Approach","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.IT","math.OC"],"primary_cat":"cs.IT","authors_text":"Dejan Vukobratovic, Mirsad Cosovic","submitted_at":"2016-05-26T15:35:28Z","abstract_excerpt":"In this paper, we propose a solution to an AC state estimation problem in electric power systems using a fully distributed Gauss-Newton method. The proposed method is placed within the context of factor graphs and belief propagation algorithms and closed-form expressions for belief propagation messages exchanged along the factor graph are derived. The obtained algorithm provides the same solution as the conventional weighted least-squares state estimation. Using a simple example, we provide a step-by-step presentation of the proposed algorithm. Finally, we discuss the convergence behaviour usi"},"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":"1605.08336","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2016-05-26T15:35:28Z","cross_cats_sorted":["math.IT","math.OC"],"title_canon_sha256":"cb04aef55514731d72ee7e264ca3ea479372783b79ad3f3c06ca8efb70953819","abstract_canon_sha256":"c48a047b8a1eb3f30dbb701a17541e0bc7af903e11243b189f04dea60ff6148d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:13:31.844614Z","signature_b64":"t/m64XqjO9T3b+p3H+ehH1osQ0bgCdis53TMgcTorB8UoIeToR1LtyCWp+O6ewSMdqIbWZNidjy2Ns4yGNgBAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d03a541f681aba1e1f098f9cca48e07597ef2caa9b099d10ef557524441b0380","last_reissued_at":"2026-05-18T01:13:31.844046Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:13:31.844046Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distributed Gauss-Newton Method for AC State Estimation: A Belief Propagation Approach","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.IT","math.OC"],"primary_cat":"cs.IT","authors_text":"Dejan Vukobratovic, Mirsad Cosovic","submitted_at":"2016-05-26T15:35:28Z","abstract_excerpt":"In this paper, we propose a solution to an AC state estimation problem in electric power systems using a fully distributed Gauss-Newton method. The proposed method is placed within the context of factor graphs and belief propagation algorithms and closed-form expressions for belief propagation messages exchanged along the factor graph are derived. The obtained algorithm provides the same solution as the conventional weighted least-squares state estimation. Using a simple example, we provide a step-by-step presentation of the proposed algorithm. Finally, we discuss the convergence behaviour usi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.08336","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":""},"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":"1605.08336","created_at":"2026-05-18T01:13:31.844106+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.08336v1","created_at":"2026-05-18T01:13:31.844106+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.08336","created_at":"2026-05-18T01:13:31.844106+00:00"},{"alias_kind":"pith_short_12","alias_value":"2A5FIH3IDK5B","created_at":"2026-05-18T12:29:52.810259+00:00"},{"alias_kind":"pith_short_16","alias_value":"2A5FIH3IDK5B4HYJ","created_at":"2026-05-18T12:29:52.810259+00:00"},{"alias_kind":"pith_short_8","alias_value":"2A5FIH3I","created_at":"2026-05-18T12:29:52.810259+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/2A5FIH3IDK5B4HYJR6OMUSHAOW","json":"https://pith.science/pith/2A5FIH3IDK5B4HYJR6OMUSHAOW.json","graph_json":"https://pith.science/api/pith-number/2A5FIH3IDK5B4HYJR6OMUSHAOW/graph.json","events_json":"https://pith.science/api/pith-number/2A5FIH3IDK5B4HYJR6OMUSHAOW/events.json","paper":"https://pith.science/paper/2A5FIH3I"},"agent_actions":{"view_html":"https://pith.science/pith/2A5FIH3IDK5B4HYJR6OMUSHAOW","download_json":"https://pith.science/pith/2A5FIH3IDK5B4HYJR6OMUSHAOW.json","view_paper":"https://pith.science/paper/2A5FIH3I","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.08336&json=true","fetch_graph":"https://pith.science/api/pith-number/2A5FIH3IDK5B4HYJR6OMUSHAOW/graph.json","fetch_events":"https://pith.science/api/pith-number/2A5FIH3IDK5B4HYJR6OMUSHAOW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2A5FIH3IDK5B4HYJR6OMUSHAOW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2A5FIH3IDK5B4HYJR6OMUSHAOW/action/storage_attestation","attest_author":"https://pith.science/pith/2A5FIH3IDK5B4HYJR6OMUSHAOW/action/author_attestation","sign_citation":"https://pith.science/pith/2A5FIH3IDK5B4HYJR6OMUSHAOW/action/citation_signature","submit_replication":"https://pith.science/pith/2A5FIH3IDK5B4HYJR6OMUSHAOW/action/replication_record"}},"created_at":"2026-05-18T01:13:31.844106+00:00","updated_at":"2026-05-18T01:13:31.844106+00:00"}