{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:PP7ELGARLYJNLBNAISIP4JUV6H","short_pith_number":"pith:PP7ELGAR","schema_version":"1.0","canonical_sha256":"7bfe4598115e12d585a04490fe2695f1ffc0e574b9e2a81844703fb358bc3df0","source":{"kind":"arxiv","id":"2606.12694","version":1},"attestation_state":"computed","paper":{"title":"A unified complexity bound for logconcave sampling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","math.PR","stat.ML"],"primary_cat":"cs.DS","authors_text":"Santosh S. Vempala, Yunbum Kook","submitted_at":"2026-06-10T21:28:30Z","abstract_excerpt":"We give a simple, unified, and nearly tight bound for sampling arbitrary logconcave distributions from a warm start using the In-and-Out algorithm along with exponential lifting. The main new ingredient in the analysis is an improved bound on the Poincar\\'e constant of a lifted distribution. As a consequence, the resulting convergence rate is nearly tight for both constrained settings (e.g., Gaussian restricted to a convex body) and well-conditioned settings (e.g., strongly logconcave and smooth densities)."},"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":"2606.12694","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DS","submitted_at":"2026-06-10T21:28:30Z","cross_cats_sorted":["cs.LG","math.PR","stat.ML"],"title_canon_sha256":"bf89c32e5335468ce6866cd0d2aa2a0de67467d2f6ec1abbfd12e96d0a32cc50","abstract_canon_sha256":"ae8ad765c1efeedbc77106cc763d1eed937104bde17517224fc47dfc4b19c86e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-12T01:08:45.827038Z","signature_b64":"tnIIEeT9q9T4hSVzXn6jL2lHXyVMlQEI2k4GULQqFL3dcw3wjs8U3atxDCi+vijCm3ljJY13fPvPdLn+PqEABw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7bfe4598115e12d585a04490fe2695f1ffc0e574b9e2a81844703fb358bc3df0","last_reissued_at":"2026-06-12T01:08:45.826215Z","signature_status":"signed_v1","first_computed_at":"2026-06-12T01:08:45.826215Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A unified complexity bound for logconcave sampling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","math.PR","stat.ML"],"primary_cat":"cs.DS","authors_text":"Santosh S. Vempala, Yunbum Kook","submitted_at":"2026-06-10T21:28:30Z","abstract_excerpt":"We give a simple, unified, and nearly tight bound for sampling arbitrary logconcave distributions from a warm start using the In-and-Out algorithm along with exponential lifting. The main new ingredient in the analysis is an improved bound on the Poincar\\'e constant of a lifted distribution. As a consequence, the resulting convergence rate is nearly tight for both constrained settings (e.g., Gaussian restricted to a convex body) and well-conditioned settings (e.g., strongly logconcave and smooth densities)."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.12694","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/2606.12694/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":"2606.12694","created_at":"2026-06-12T01:08:45.826362+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.12694v1","created_at":"2026-06-12T01:08:45.826362+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.12694","created_at":"2026-06-12T01:08:45.826362+00:00"},{"alias_kind":"pith_short_12","alias_value":"PP7ELGARLYJN","created_at":"2026-06-12T01:08:45.826362+00:00"},{"alias_kind":"pith_short_16","alias_value":"PP7ELGARLYJNLBNA","created_at":"2026-06-12T01:08:45.826362+00:00"},{"alias_kind":"pith_short_8","alias_value":"PP7ELGAR","created_at":"2026-06-12T01:08:45.826362+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/PP7ELGARLYJNLBNAISIP4JUV6H","json":"https://pith.science/pith/PP7ELGARLYJNLBNAISIP4JUV6H.json","graph_json":"https://pith.science/api/pith-number/PP7ELGARLYJNLBNAISIP4JUV6H/graph.json","events_json":"https://pith.science/api/pith-number/PP7ELGARLYJNLBNAISIP4JUV6H/events.json","paper":"https://pith.science/paper/PP7ELGAR"},"agent_actions":{"view_html":"https://pith.science/pith/PP7ELGARLYJNLBNAISIP4JUV6H","download_json":"https://pith.science/pith/PP7ELGARLYJNLBNAISIP4JUV6H.json","view_paper":"https://pith.science/paper/PP7ELGAR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.12694&json=true","fetch_graph":"https://pith.science/api/pith-number/PP7ELGARLYJNLBNAISIP4JUV6H/graph.json","fetch_events":"https://pith.science/api/pith-number/PP7ELGARLYJNLBNAISIP4JUV6H/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PP7ELGARLYJNLBNAISIP4JUV6H/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PP7ELGARLYJNLBNAISIP4JUV6H/action/storage_attestation","attest_author":"https://pith.science/pith/PP7ELGARLYJNLBNAISIP4JUV6H/action/author_attestation","sign_citation":"https://pith.science/pith/PP7ELGARLYJNLBNAISIP4JUV6H/action/citation_signature","submit_replication":"https://pith.science/pith/PP7ELGARLYJNLBNAISIP4JUV6H/action/replication_record"}},"created_at":"2026-06-12T01:08:45.826362+00:00","updated_at":"2026-06-12T01:08:45.826362+00:00"}