{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:DNX6FEQ7LD64YURUF5YZMCAWHB","short_pith_number":"pith:DNX6FEQ7","canonical_record":{"source":{"id":"2202.11258","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-02-23T01:20:13Z","cross_cats_sorted":["stat.CO","stat.ML"],"title_canon_sha256":"1f0fd530dc0efaee051354bf4522e7276f2447767f90a99afa8091419a3b87fd","abstract_canon_sha256":"b7193a8f8421d5443f64006e4a27702aa161ed3e9f6d85f64f0e8cf40cacf94f"},"schema_version":"1.0"},"canonical_sha256":"1b6fe2921f58fdcc52342f71960816387d5675fbd7245c58c39cc467ee94c3be","source":{"kind":"arxiv","id":"2202.11258","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.11258","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"arxiv_version","alias_value":"2202.11258v1","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.11258","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"pith_short_12","alias_value":"DNX6FEQ7LD64","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"pith_short_16","alias_value":"DNX6FEQ7LD64YURU","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"pith_short_8","alias_value":"DNX6FEQ7","created_at":"2026-07-05T03:59:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:DNX6FEQ7LD64YURUF5YZMCAWHB","target":"record","payload":{"canonical_record":{"source":{"id":"2202.11258","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-02-23T01:20:13Z","cross_cats_sorted":["stat.CO","stat.ML"],"title_canon_sha256":"1f0fd530dc0efaee051354bf4522e7276f2447767f90a99afa8091419a3b87fd","abstract_canon_sha256":"b7193a8f8421d5443f64006e4a27702aa161ed3e9f6d85f64f0e8cf40cacf94f"},"schema_version":"1.0"},"canonical_sha256":"1b6fe2921f58fdcc52342f71960816387d5675fbd7245c58c39cc467ee94c3be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:59:30.240438Z","signature_b64":"MgK+JiNgl5Zy/LoeeO4d8EnRFLVirs62Sceqy9nRHbzLjwddSIxPODKzIUu9bgBY2h4Gb7lCy+qev0GuaS5hBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1b6fe2921f58fdcc52342f71960816387d5675fbd7245c58c39cc467ee94c3be","last_reissued_at":"2026-07-05T03:59:30.239953Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:59:30.239953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.11258","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:59:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gR5w4C7piIFmKo45ybO575RjCWImJAJEYk20pdhXajFtMtNNrGLzQvyZ0y/BYsonHxo2epxvgYrc98AhsZVGCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T11:43:04.986525Z"},"content_sha256":"19ff29dbb195ab6949d845ae1d18f3784d425abd3fff6ef3fde7a66067d2fbdf","schema_version":"1.0","event_id":"sha256:19ff29dbb195ab6949d845ae1d18f3784d425abd3fff6ef3fde7a66067d2fbdf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:DNX6FEQ7LD64YURUF5YZMCAWHB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Many processors, little time: MCMC for partitions via optimal transport couplings","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.CO","stat.ML"],"primary_cat":"stat.ME","authors_text":"Brian L. Trippe, Tamara Broderick, Tin D. Nguyen","submitted_at":"2022-02-23T01:20:13Z","abstract_excerpt":"Markov chain Monte Carlo (MCMC) methods are often used in clustering since they guarantee asymptotically exact expectations in the infinite-time limit. In finite time, though, slow mixing often leads to poor performance. Modern computing environments offer massive parallelism, but naive implementations of parallel MCMC can exhibit substantial bias. In MCMC samplers of continuous random variables, Markov chain couplings can overcome bias. But these approaches depend crucially on paired chains meetings after a small number of transitions. We show that straightforward applications of existing cou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.11258","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/2202.11258/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:59:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"arO+89ZoZDw9DH804lK1GajQ/At7SgTiBVM+364dHHN1U3euQ0C1wfH0u8NU+iA+xuWkxxYm/HJT8Xg4YvaoDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T11:43:04.986909Z"},"content_sha256":"6261943741b793edf3cbc3f5ca7c42fc379e4fb2c942a69a5902799d0464180d","schema_version":"1.0","event_id":"sha256:6261943741b793edf3cbc3f5ca7c42fc379e4fb2c942a69a5902799d0464180d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DNX6FEQ7LD64YURUF5YZMCAWHB/bundle.json","state_url":"https://pith.science/pith/DNX6FEQ7LD64YURUF5YZMCAWHB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DNX6FEQ7LD64YURUF5YZMCAWHB/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":"2026-08-13T11:43:04Z","links":{"resolver":"https://pith.science/pith/DNX6FEQ7LD64YURUF5YZMCAWHB","bundle":"https://pith.science/pith/DNX6FEQ7LD64YURUF5YZMCAWHB/bundle.json","state":"https://pith.science/pith/DNX6FEQ7LD64YURUF5YZMCAWHB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DNX6FEQ7LD64YURUF5YZMCAWHB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:DNX6FEQ7LD64YURUF5YZMCAWHB","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":"b7193a8f8421d5443f64006e4a27702aa161ed3e9f6d85f64f0e8cf40cacf94f","cross_cats_sorted":["stat.CO","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-02-23T01:20:13Z","title_canon_sha256":"1f0fd530dc0efaee051354bf4522e7276f2447767f90a99afa8091419a3b87fd"},"schema_version":"1.0","source":{"id":"2202.11258","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.11258","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"arxiv_version","alias_value":"2202.11258v1","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.11258","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"pith_short_12","alias_value":"DNX6FEQ7LD64","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"pith_short_16","alias_value":"DNX6FEQ7LD64YURU","created_at":"2026-07-05T03:59:30Z"},{"alias_kind":"pith_short_8","alias_value":"DNX6FEQ7","created_at":"2026-07-05T03:59:30Z"}],"graph_snapshots":[{"event_id":"sha256:6261943741b793edf3cbc3f5ca7c42fc379e4fb2c942a69a5902799d0464180d","target":"graph","created_at":"2026-07-05T03:59:30Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2202.11258/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Markov chain Monte Carlo (MCMC) methods are often used in clustering since they guarantee asymptotically exact expectations in the infinite-time limit. In finite time, though, slow mixing often leads to poor performance. Modern computing environments offer massive parallelism, but naive implementations of parallel MCMC can exhibit substantial bias. In MCMC samplers of continuous random variables, Markov chain couplings can overcome bias. But these approaches depend crucially on paired chains meetings after a small number of transitions. We show that straightforward applications of existing cou","authors_text":"Brian L. Trippe, Tamara Broderick, Tin D. Nguyen","cross_cats":["stat.CO","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-02-23T01:20:13Z","title":"Many processors, little time: MCMC for partitions via optimal transport couplings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.11258","kind":"arxiv","version":1},"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":"sha256:19ff29dbb195ab6949d845ae1d18f3784d425abd3fff6ef3fde7a66067d2fbdf","target":"record","created_at":"2026-07-05T03:59:30Z","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":"b7193a8f8421d5443f64006e4a27702aa161ed3e9f6d85f64f0e8cf40cacf94f","cross_cats_sorted":["stat.CO","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-02-23T01:20:13Z","title_canon_sha256":"1f0fd530dc0efaee051354bf4522e7276f2447767f90a99afa8091419a3b87fd"},"schema_version":"1.0","source":{"id":"2202.11258","kind":"arxiv","version":1}},"canonical_sha256":"1b6fe2921f58fdcc52342f71960816387d5675fbd7245c58c39cc467ee94c3be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1b6fe2921f58fdcc52342f71960816387d5675fbd7245c58c39cc467ee94c3be","first_computed_at":"2026-07-05T03:59:30.239953Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:59:30.239953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MgK+JiNgl5Zy/LoeeO4d8EnRFLVirs62Sceqy9nRHbzLjwddSIxPODKzIUu9bgBY2h4Gb7lCy+qev0GuaS5hBg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:59:30.240438Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.11258","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:19ff29dbb195ab6949d845ae1d18f3784d425abd3fff6ef3fde7a66067d2fbdf","sha256:6261943741b793edf3cbc3f5ca7c42fc379e4fb2c942a69a5902799d0464180d"],"state_sha256":"eb82363bb6fd8bff7c79518fb8b063e30b141d269c950ca57483a291c14c79ca"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"szAvL643pP8AmN9QSeYRejyo6WQJGcSTrDMTfuG8sRTo02OGOBDorwwO612fQSb/dFFXmwULl3KmLWHB1+qmDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T11:43:04.989627Z","bundle_sha256":"ef16452e63162f8fba24b7c9336eee617f6e2b467a947c048f3988be3ddb019e"}}