{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:HIPHLZAJ46CCIGR54E3VFBBWK5","short_pith_number":"pith:HIPHLZAJ","schema_version":"1.0","canonical_sha256":"3a1e75e409e784241a3de1375284365768abdb09f86da5af5f3440e4b0fa3673","source":{"kind":"arxiv","id":"1307.7089","version":1},"attestation_state":"computed","paper":{"title":"An approximation algorithm for the Bandpass-2 problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Guohui Lin, Jiuping Xu, Lusheng Wang, Randy Goebel, Weitian Tong, Yinfeng Xu, Zhi-Zhong Chen","submitted_at":"2013-07-26T16:46:04Z","abstract_excerpt":"The general Bandpass-$B$ problem is NP-hard and can be approximated by a reduction into the weighted $B$-set packing problem, with a worst case performance ratio of $O(B^2)$. When $B = 2$, a maximum weight matching gives a 2-approximation to the problem. In this paper, we call the Bandpass-2 problem simply the Bandpass problem. The Bandpass problem can be viewed as a variation of the maximum traveling salesman problem, in which the edge weights are dynamic rather than given at the front. We present a ${426}{227}$-approximation algorithm for the problem. Such an improved approximation is built "},"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":"1307.7089","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2013-07-26T16:46:04Z","cross_cats_sorted":[],"title_canon_sha256":"1e5882d3b961c3b1d4ddbb2fa4473c5bf74beeb5a60b1ac2cb61ea22484018da","abstract_canon_sha256":"3a8f4d9f0d038faa1d853acadb9a1dd4931eaa1af667bf87588a780623dea3fc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:17:25.381243Z","signature_b64":"QkwR9mYz1WzInar/0m6qJQlu0L/MT8pWDjF2dOn//OM9E4kkIDl+877NHg40Mi1I7QwCeOyawaD/2TGDkPxABA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a1e75e409e784241a3de1375284365768abdb09f86da5af5f3440e4b0fa3673","last_reissued_at":"2026-05-18T03:17:25.380672Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:17:25.380672Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An approximation algorithm for the Bandpass-2 problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Guohui Lin, Jiuping Xu, Lusheng Wang, Randy Goebel, Weitian Tong, Yinfeng Xu, Zhi-Zhong Chen","submitted_at":"2013-07-26T16:46:04Z","abstract_excerpt":"The general Bandpass-$B$ problem is NP-hard and can be approximated by a reduction into the weighted $B$-set packing problem, with a worst case performance ratio of $O(B^2)$. When $B = 2$, a maximum weight matching gives a 2-approximation to the problem. In this paper, we call the Bandpass-2 problem simply the Bandpass problem. The Bandpass problem can be viewed as a variation of the maximum traveling salesman problem, in which the edge weights are dynamic rather than given at the front. We present a ${426}{227}$-approximation algorithm for the problem. Such an improved approximation is built "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1307.7089","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":"1307.7089","created_at":"2026-05-18T03:17:25.380773+00:00"},{"alias_kind":"arxiv_version","alias_value":"1307.7089v1","created_at":"2026-05-18T03:17:25.380773+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1307.7089","created_at":"2026-05-18T03:17:25.380773+00:00"},{"alias_kind":"pith_short_12","alias_value":"HIPHLZAJ46CC","created_at":"2026-05-18T12:27:46.883200+00:00"},{"alias_kind":"pith_short_16","alias_value":"HIPHLZAJ46CCIGR5","created_at":"2026-05-18T12:27:46.883200+00:00"},{"alias_kind":"pith_short_8","alias_value":"HIPHLZAJ","created_at":"2026-05-18T12:27:46.883200+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/HIPHLZAJ46CCIGR54E3VFBBWK5","json":"https://pith.science/pith/HIPHLZAJ46CCIGR54E3VFBBWK5.json","graph_json":"https://pith.science/api/pith-number/HIPHLZAJ46CCIGR54E3VFBBWK5/graph.json","events_json":"https://pith.science/api/pith-number/HIPHLZAJ46CCIGR54E3VFBBWK5/events.json","paper":"https://pith.science/paper/HIPHLZAJ"},"agent_actions":{"view_html":"https://pith.science/pith/HIPHLZAJ46CCIGR54E3VFBBWK5","download_json":"https://pith.science/pith/HIPHLZAJ46CCIGR54E3VFBBWK5.json","view_paper":"https://pith.science/paper/HIPHLZAJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1307.7089&json=true","fetch_graph":"https://pith.science/api/pith-number/HIPHLZAJ46CCIGR54E3VFBBWK5/graph.json","fetch_events":"https://pith.science/api/pith-number/HIPHLZAJ46CCIGR54E3VFBBWK5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HIPHLZAJ46CCIGR54E3VFBBWK5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HIPHLZAJ46CCIGR54E3VFBBWK5/action/storage_attestation","attest_author":"https://pith.science/pith/HIPHLZAJ46CCIGR54E3VFBBWK5/action/author_attestation","sign_citation":"https://pith.science/pith/HIPHLZAJ46CCIGR54E3VFBBWK5/action/citation_signature","submit_replication":"https://pith.science/pith/HIPHLZAJ46CCIGR54E3VFBBWK5/action/replication_record"}},"created_at":"2026-05-18T03:17:25.380773+00:00","updated_at":"2026-05-18T03:17:25.380773+00:00"}