{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:UAHBRO5QVBWIMNYN6VCJOMFUK6","short_pith_number":"pith:UAHBRO5Q","canonical_record":{"source":{"id":"1404.2396","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2014-04-09T08:48:51Z","cross_cats_sorted":[],"title_canon_sha256":"7802bc8bc79ec942c9f5e5fc736fd5144083a2ce77ea017976cb5ec90822726e","abstract_canon_sha256":"71fc56c396d0cb0371c0c49ebd69ecab2fc31e4420b8b1ff56cc3ee3c76553d1"},"schema_version":"1.0"},"canonical_sha256":"a00e18bbb0a86c86370df5449730b4578847fe1e5cc4901d000b666e08371252","source":{"kind":"arxiv","id":"1404.2396","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1404.2396","created_at":"2026-05-18T02:49:46Z"},{"alias_kind":"arxiv_version","alias_value":"1404.2396v2","created_at":"2026-05-18T02:49:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1404.2396","created_at":"2026-05-18T02:49:46Z"},{"alias_kind":"pith_short_12","alias_value":"UAHBRO5QVBWI","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_16","alias_value":"UAHBRO5QVBWIMNYN","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_8","alias_value":"UAHBRO5Q","created_at":"2026-05-18T12:28:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:UAHBRO5QVBWIMNYN6VCJOMFUK6","target":"record","payload":{"canonical_record":{"source":{"id":"1404.2396","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2014-04-09T08:48:51Z","cross_cats_sorted":[],"title_canon_sha256":"7802bc8bc79ec942c9f5e5fc736fd5144083a2ce77ea017976cb5ec90822726e","abstract_canon_sha256":"71fc56c396d0cb0371c0c49ebd69ecab2fc31e4420b8b1ff56cc3ee3c76553d1"},"schema_version":"1.0"},"canonical_sha256":"a00e18bbb0a86c86370df5449730b4578847fe1e5cc4901d000b666e08371252","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:49:46.898448Z","signature_b64":"7teY5nY5q2IP74INxXr/pmk1sSSiwtHQkOBaoor+m4JUZ/nLzYWndY6QFF1jHW3tR9FWKdF7L3o+AFcCrxqPAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a00e18bbb0a86c86370df5449730b4578847fe1e5cc4901d000b666e08371252","last_reissued_at":"2026-05-18T02:49:46.898057Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:49:46.898057Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1404.2396","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:49:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q+YYBtFJJBOuDgx1khQ6s3G0/HM3dSuAQ3y7/BMc0CbBVLZzifLG1N4BtX6R9kjz/Z7xrBVvZWxr2E67hjYKBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T22:31:17.044258Z"},"content_sha256":"e4c0cca16dd4fad0ad30a337951558c18fe107773ebb71638e528c0cfac76ecf","schema_version":"1.0","event_id":"sha256:e4c0cca16dd4fad0ad30a337951558c18fe107773ebb71638e528c0cfac76ecf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:UAHBRO5QVBWIMNYN6VCJOMFUK6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Approximating the Regular Graphic TSP in near linear time","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Ashish Chiplunkar, Sundar Vishwanathan","submitted_at":"2014-04-09T08:48:51Z","abstract_excerpt":"We present a randomized approximation algorithm for computing traveling salesperson tours in undirected regular graphs. Given an $n$-vertex, $k$-regular graph, the algorithm computes a tour of length at most $\\left(1+\\frac{7}{\\ln k-O(1)}\\right)n$, with high probability, in $O(nk \\log k)$ time. This improves upon a recent result by Vishnoi (\\cite{Vishnoi12}, FOCS 2012) for the same problem, in terms of both approximation factor, and running time. The key ingredient of our algorithm is a technique that uses edge-coloring algorithms to sample a cycle cover with $O(n/\\log k)$ cycles with high prob"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1404.2396","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:49:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4XKTLJUwvNG1RxwqDHYCzEy5kUFXfiGT00LdIKsZXOlkMtHcKfK6q2dPW+fynljmc/u9vyO9ycWGtKqMYM9NCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T22:31:17.044625Z"},"content_sha256":"cfd417d5ae318867f038d7607e0d1dce1dc0e9a15618ebd5165957df1c82e96d","schema_version":"1.0","event_id":"sha256:cfd417d5ae318867f038d7607e0d1dce1dc0e9a15618ebd5165957df1c82e96d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UAHBRO5QVBWIMNYN6VCJOMFUK6/bundle.json","state_url":"https://pith.science/pith/UAHBRO5QVBWIMNYN6VCJOMFUK6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UAHBRO5QVBWIMNYN6VCJOMFUK6/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":"2026-06-21T22:31:17Z","links":{"resolver":"https://pith.science/pith/UAHBRO5QVBWIMNYN6VCJOMFUK6","bundle":"https://pith.science/pith/UAHBRO5QVBWIMNYN6VCJOMFUK6/bundle.json","state":"https://pith.science/pith/UAHBRO5QVBWIMNYN6VCJOMFUK6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UAHBRO5QVBWIMNYN6VCJOMFUK6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:UAHBRO5QVBWIMNYN6VCJOMFUK6","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":"71fc56c396d0cb0371c0c49ebd69ecab2fc31e4420b8b1ff56cc3ee3c76553d1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2014-04-09T08:48:51Z","title_canon_sha256":"7802bc8bc79ec942c9f5e5fc736fd5144083a2ce77ea017976cb5ec90822726e"},"schema_version":"1.0","source":{"id":"1404.2396","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1404.2396","created_at":"2026-05-18T02:49:46Z"},{"alias_kind":"arxiv_version","alias_value":"1404.2396v2","created_at":"2026-05-18T02:49:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1404.2396","created_at":"2026-05-18T02:49:46Z"},{"alias_kind":"pith_short_12","alias_value":"UAHBRO5QVBWI","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_16","alias_value":"UAHBRO5QVBWIMNYN","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_8","alias_value":"UAHBRO5Q","created_at":"2026-05-18T12:28:52Z"}],"graph_snapshots":[{"event_id":"sha256:cfd417d5ae318867f038d7607e0d1dce1dc0e9a15618ebd5165957df1c82e96d","target":"graph","created_at":"2026-05-18T02:49:46Z","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"},"paper":{"abstract_excerpt":"We present a randomized approximation algorithm for computing traveling salesperson tours in undirected regular graphs. Given an $n$-vertex, $k$-regular graph, the algorithm computes a tour of length at most $\\left(1+\\frac{7}{\\ln k-O(1)}\\right)n$, with high probability, in $O(nk \\log k)$ time. This improves upon a recent result by Vishnoi (\\cite{Vishnoi12}, FOCS 2012) for the same problem, in terms of both approximation factor, and running time. The key ingredient of our algorithm is a technique that uses edge-coloring algorithms to sample a cycle cover with $O(n/\\log k)$ cycles with high prob","authors_text":"Ashish Chiplunkar, Sundar Vishwanathan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2014-04-09T08:48:51Z","title":"Approximating the Regular Graphic TSP in near linear time"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1404.2396","kind":"arxiv","version":2},"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:e4c0cca16dd4fad0ad30a337951558c18fe107773ebb71638e528c0cfac76ecf","target":"record","created_at":"2026-05-18T02:49:46Z","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":"71fc56c396d0cb0371c0c49ebd69ecab2fc31e4420b8b1ff56cc3ee3c76553d1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2014-04-09T08:48:51Z","title_canon_sha256":"7802bc8bc79ec942c9f5e5fc736fd5144083a2ce77ea017976cb5ec90822726e"},"schema_version":"1.0","source":{"id":"1404.2396","kind":"arxiv","version":2}},"canonical_sha256":"a00e18bbb0a86c86370df5449730b4578847fe1e5cc4901d000b666e08371252","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a00e18bbb0a86c86370df5449730b4578847fe1e5cc4901d000b666e08371252","first_computed_at":"2026-05-18T02:49:46.898057Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:49:46.898057Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7teY5nY5q2IP74INxXr/pmk1sSSiwtHQkOBaoor+m4JUZ/nLzYWndY6QFF1jHW3tR9FWKdF7L3o+AFcCrxqPAA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:49:46.898448Z","signed_message":"canonical_sha256_bytes"},"source_id":"1404.2396","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4c0cca16dd4fad0ad30a337951558c18fe107773ebb71638e528c0cfac76ecf","sha256:cfd417d5ae318867f038d7607e0d1dce1dc0e9a15618ebd5165957df1c82e96d"],"state_sha256":"6c28a78b88ec1f08e41b7a36dd54f9a8363792ae3a0dd20f45ef799618154b13"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7MPjNk+8hyVEITbyy57JwbsVfkLs3vG4RpDXY+IVv5pPRwNUgPbZX4MZql1EbJxVo36+xVZ/rg52xETNnrerDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-21T22:31:17.046647Z","bundle_sha256":"e9c9a76f2882159300cd052c08e1ac253ec5eb5da6a44f698c6d811c9d18ea24"}}