{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:MCFD6CUAVFYJQ45HHIDDCO2R7J","short_pith_number":"pith:MCFD6CUA","schema_version":"1.0","canonical_sha256":"608a3f0a80a9709873a73a06313b51fa4585a233d9a20bf783585ac72c59dcc8","source":{"kind":"arxiv","id":"1403.6188","version":2},"attestation_state":"computed","paper":{"title":"Brief Announcement: Almost-Tight Approximation Distributed Algorithm for Minimum Cut","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Danupon Nanongkai","submitted_at":"2014-03-24T23:18:37Z","abstract_excerpt":"In this short paper, we present an improved algorithm for approximating the minimum cut on distributed (CONGEST) networks. Let $\\lambda$ be the minimum cut. Our algorithm can compute $\\lambda$ exactly in $\\tilde{O}((\\sqrt{n}+D)\\poly(\\lambda))$ time, where $n$ is the number of nodes (processors) in the network, $D$ is the network diameter, and $\\tilde{O}$ hides $\\poly\\log n$. By a standard reduction, we can convert this algorithm into a $(1+\\epsilon)$-approximation $\\tilde{O}((\\sqrt{n}+D)/\\poly(\\epsilon))$-time algorithm. The latter result improves over the previous $(2+\\epsilon)$-approximation"},"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":"1403.6188","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2014-03-24T23:18:37Z","cross_cats_sorted":[],"title_canon_sha256":"ecb8a1ef77dabfe18824b7ad890b505986da98375ab6c7ba156aba5bb49f4e9b","abstract_canon_sha256":"1b3ed4fca913e89ccc95b13b7618039b77e9ffceaa8359c21b9f1a3e2b40017a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:51:49.425909Z","signature_b64":"kFshDTHUtfkNU2Gp80dt2dXMpMWxJTKEDqIP3UdskJgTo4kS9/b9mmealpgdGQukbxR/l7ZSRSHZn2OyuNwoDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"608a3f0a80a9709873a73a06313b51fa4585a233d9a20bf783585ac72c59dcc8","last_reissued_at":"2026-05-18T02:51:49.425456Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:51:49.425456Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Brief Announcement: Almost-Tight Approximation Distributed Algorithm for Minimum Cut","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Danupon Nanongkai","submitted_at":"2014-03-24T23:18:37Z","abstract_excerpt":"In this short paper, we present an improved algorithm for approximating the minimum cut on distributed (CONGEST) networks. Let $\\lambda$ be the minimum cut. Our algorithm can compute $\\lambda$ exactly in $\\tilde{O}((\\sqrt{n}+D)\\poly(\\lambda))$ time, where $n$ is the number of nodes (processors) in the network, $D$ is the network diameter, and $\\tilde{O}$ hides $\\poly\\log n$. By a standard reduction, we can convert this algorithm into a $(1+\\epsilon)$-approximation $\\tilde{O}((\\sqrt{n}+D)/\\poly(\\epsilon))$-time algorithm. The latter result improves over the previous $(2+\\epsilon)$-approximation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1403.6188","kind":"arxiv","version":2},"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":"1403.6188","created_at":"2026-05-18T02:51:49.425532+00:00"},{"alias_kind":"arxiv_version","alias_value":"1403.6188v2","created_at":"2026-05-18T02:51:49.425532+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1403.6188","created_at":"2026-05-18T02:51:49.425532+00:00"},{"alias_kind":"pith_short_12","alias_value":"MCFD6CUAVFYJ","created_at":"2026-05-18T12:28:38.356838+00:00"},{"alias_kind":"pith_short_16","alias_value":"MCFD6CUAVFYJQ45H","created_at":"2026-05-18T12:28:38.356838+00:00"},{"alias_kind":"pith_short_8","alias_value":"MCFD6CUA","created_at":"2026-05-18T12:28:38.356838+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/MCFD6CUAVFYJQ45HHIDDCO2R7J","json":"https://pith.science/pith/MCFD6CUAVFYJQ45HHIDDCO2R7J.json","graph_json":"https://pith.science/api/pith-number/MCFD6CUAVFYJQ45HHIDDCO2R7J/graph.json","events_json":"https://pith.science/api/pith-number/MCFD6CUAVFYJQ45HHIDDCO2R7J/events.json","paper":"https://pith.science/paper/MCFD6CUA"},"agent_actions":{"view_html":"https://pith.science/pith/MCFD6CUAVFYJQ45HHIDDCO2R7J","download_json":"https://pith.science/pith/MCFD6CUAVFYJQ45HHIDDCO2R7J.json","view_paper":"https://pith.science/paper/MCFD6CUA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1403.6188&json=true","fetch_graph":"https://pith.science/api/pith-number/MCFD6CUAVFYJQ45HHIDDCO2R7J/graph.json","fetch_events":"https://pith.science/api/pith-number/MCFD6CUAVFYJQ45HHIDDCO2R7J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MCFD6CUAVFYJQ45HHIDDCO2R7J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MCFD6CUAVFYJQ45HHIDDCO2R7J/action/storage_attestation","attest_author":"https://pith.science/pith/MCFD6CUAVFYJQ45HHIDDCO2R7J/action/author_attestation","sign_citation":"https://pith.science/pith/MCFD6CUAVFYJQ45HHIDDCO2R7J/action/citation_signature","submit_replication":"https://pith.science/pith/MCFD6CUAVFYJQ45HHIDDCO2R7J/action/replication_record"}},"created_at":"2026-05-18T02:51:49.425532+00:00","updated_at":"2026-05-18T02:51:49.425532+00:00"}