{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:MVHXIG5XD3QFG2LCIECYZHCRO3","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":"323e609274a22412bd9dcbf8515140789359c9db80703ce3ccb44365f81a0dbe","cross_cats_sorted":["stat.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2012-10-03T17:48:12Z","title_canon_sha256":"4ab20419e1b980af3fd2d30e17a2d624a12294d74da3b78c27458d2ce9476536"},"schema_version":"1.0","source":{"id":"1210.1180","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1210.1180","created_at":"2026-05-18T03:02:07Z"},{"alias_kind":"arxiv_version","alias_value":"1210.1180v2","created_at":"2026-05-18T03:02:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1210.1180","created_at":"2026-05-18T03:02:07Z"},{"alias_kind":"pith_short_12","alias_value":"MVHXIG5XD3QF","created_at":"2026-05-18T12:27:14Z"},{"alias_kind":"pith_short_16","alias_value":"MVHXIG5XD3QFG2LC","created_at":"2026-05-18T12:27:14Z"},{"alias_kind":"pith_short_8","alias_value":"MVHXIG5X","created_at":"2026-05-18T12:27:14Z"}],"graph_snapshots":[{"event_id":"sha256:4dd39674ed03aeac915d930bcf03a85299136ed3268a08f601f6bf02168ca929","target":"graph","created_at":"2026-05-18T03:02:07Z","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":"The Metropolis-adjusted Langevin algorithm (MALA) is a Metropolis-Hastings method for approximate sampling from continuous distributions. We derive upper bounds for the contraction rate in Kantorovich-Rubinstein-Wasserstein distance of the MALA chain with semi-implicit Euler proposals applied to log-concave probability measures that have a density w.r.t. a Gaussian reference measure. For sufficiently \"regular\" densities, the estimates are dimension-independent, and they hold for sufficiently small step sizes $h$ that do not depend on the dimension either. In the limit $h\\downarrow0$, the bound","authors_text":"Andreas Eberle","cross_cats":["stat.CO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2012-10-03T17:48:12Z","title":"Error bounds for Metropolis-Hastings algorithms applied to perturbations of Gaussian measures in high dimensions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1210.1180","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":"sha256:246ff14076cff864649e17c6cf1fa0ee8112ffb4b31551a6c36c9ca7bfa4c9a1","target":"record","created_at":"2026-05-18T03:02:07Z","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":"323e609274a22412bd9dcbf8515140789359c9db80703ce3ccb44365f81a0dbe","cross_cats_sorted":["stat.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2012-10-03T17:48:12Z","title_canon_sha256":"4ab20419e1b980af3fd2d30e17a2d624a12294d74da3b78c27458d2ce9476536"},"schema_version":"1.0","source":{"id":"1210.1180","kind":"arxiv","version":2}},"canonical_sha256":"654f741bb71ee053696241058c9c5176c40047e455e954d3b02bb81f52a5f532","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"654f741bb71ee053696241058c9c5176c40047e455e954d3b02bb81f52a5f532","first_computed_at":"2026-05-18T03:02:07.515858Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:02:07.515858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0u3zz9GtHAEIwCu9cXiK4lBfG1Wp8+XIKxqZ5FAy/f3Ql8CJZPezS4ANZwKCSHxLarGUXayh4zCeKjP+kCErAw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:02:07.516592Z","signed_message":"canonical_sha256_bytes"},"source_id":"1210.1180","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:246ff14076cff864649e17c6cf1fa0ee8112ffb4b31551a6c36c9ca7bfa4c9a1","sha256:4dd39674ed03aeac915d930bcf03a85299136ed3268a08f601f6bf02168ca929"],"state_sha256":"2d7b78a5814ffb4f5a94075ed81046016b01448532ff13507c6580f4b7d9070c"}