{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:DKQ36RMZUHKDKRKOP3SP3V62M4","short_pith_number":"pith:DKQ36RMZ","schema_version":"1.0","canonical_sha256":"1aa1bf4599a1d435454e7ee4fdd7da673ff0a94e662ac665d9f39bdcdeaa547d","source":{"kind":"arxiv","id":"2508.13841","version":1},"attestation_state":"computed","paper":{"title":"Optimal Candidate Positioning in Multi-Issue Elections","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Bart de Keijzer, Colin Cleveland, Maria Polukarov","submitted_at":"2025-08-19T14:01:57Z","abstract_excerpt":"We study strategic candidate positioning in multidimensional spatial-voting elections. Voters and candidates are represented as points in $\\mathbb{R}^d$, and each voter supports the candidate that is closest under a distance induced by an $\\ell_p$-norm. We prove that computing an optimal location for a new candidate is NP-hard already against a single opponent, whereas for a constant number of issues the problem is tractable: an $O(n^{d+1})$ hyperplane-enumeration algorithm and an $O(n \\log n)$ radial-sweep routine for $d=2$ solve the task exactly. We further derive the first approximation gua"},"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":"2508.13841","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2025-08-19T14:01:57Z","cross_cats_sorted":[],"title_canon_sha256":"3c2fe51ff644e69ba65c34ad603325ed2980448f32af09775583ca21af8f3e7c","abstract_canon_sha256":"e04cbe5d584f1a61c9f7bd9cb9fe4d619f2381d335f00b408e8ab7fd0f1d4f68"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:56:08.469375Z","signature_b64":"yXBnF++wfviU6bnuZMUOYHiVNrKxidqBfHBso8F+sgUzGXNrOHFJ4DUGqdXzcGwGOj7xtvbyRQnqqF99ZWgdBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1aa1bf4599a1d435454e7ee4fdd7da673ff0a94e662ac665d9f39bdcdeaa547d","last_reissued_at":"2026-07-05T11:56:08.468974Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:56:08.468974Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimal Candidate Positioning in Multi-Issue Elections","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Bart de Keijzer, Colin Cleveland, Maria Polukarov","submitted_at":"2025-08-19T14:01:57Z","abstract_excerpt":"We study strategic candidate positioning in multidimensional spatial-voting elections. Voters and candidates are represented as points in $\\mathbb{R}^d$, and each voter supports the candidate that is closest under a distance induced by an $\\ell_p$-norm. We prove that computing an optimal location for a new candidate is NP-hard already against a single opponent, whereas for a constant number of issues the problem is tractable: an $O(n^{d+1})$ hyperplane-enumeration algorithm and an $O(n \\log n)$ radial-sweep routine for $d=2$ solve the task exactly. We further derive the first approximation gua"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.13841","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2508.13841/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2508.13841","created_at":"2026-07-05T11:56:08.469026+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.13841v1","created_at":"2026-07-05T11:56:08.469026+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.13841","created_at":"2026-07-05T11:56:08.469026+00:00"},{"alias_kind":"pith_short_12","alias_value":"DKQ36RMZUHKD","created_at":"2026-07-05T11:56:08.469026+00:00"},{"alias_kind":"pith_short_16","alias_value":"DKQ36RMZUHKDKRKO","created_at":"2026-07-05T11:56:08.469026+00:00"},{"alias_kind":"pith_short_8","alias_value":"DKQ36RMZ","created_at":"2026-07-05T11:56:08.469026+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/DKQ36RMZUHKDKRKOP3SP3V62M4","json":"https://pith.science/pith/DKQ36RMZUHKDKRKOP3SP3V62M4.json","graph_json":"https://pith.science/api/pith-number/DKQ36RMZUHKDKRKOP3SP3V62M4/graph.json","events_json":"https://pith.science/api/pith-number/DKQ36RMZUHKDKRKOP3SP3V62M4/events.json","paper":"https://pith.science/paper/DKQ36RMZ"},"agent_actions":{"view_html":"https://pith.science/pith/DKQ36RMZUHKDKRKOP3SP3V62M4","download_json":"https://pith.science/pith/DKQ36RMZUHKDKRKOP3SP3V62M4.json","view_paper":"https://pith.science/paper/DKQ36RMZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.13841&json=true","fetch_graph":"https://pith.science/api/pith-number/DKQ36RMZUHKDKRKOP3SP3V62M4/graph.json","fetch_events":"https://pith.science/api/pith-number/DKQ36RMZUHKDKRKOP3SP3V62M4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DKQ36RMZUHKDKRKOP3SP3V62M4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DKQ36RMZUHKDKRKOP3SP3V62M4/action/storage_attestation","attest_author":"https://pith.science/pith/DKQ36RMZUHKDKRKOP3SP3V62M4/action/author_attestation","sign_citation":"https://pith.science/pith/DKQ36RMZUHKDKRKOP3SP3V62M4/action/citation_signature","submit_replication":"https://pith.science/pith/DKQ36RMZUHKDKRKOP3SP3V62M4/action/replication_record"}},"created_at":"2026-07-05T11:56:08.469026+00:00","updated_at":"2026-07-05T11:56:08.469026+00:00"}