{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:74H7BZZE6TMTRCBPE6NC4Q2TMX","short_pith_number":"pith:74H7BZZE","canonical_record":{"source":{"id":"1601.05633","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-01-21T13:54:17Z","cross_cats_sorted":[],"title_canon_sha256":"c755a6e8f2e2cd1cc4d9a14559456ba8236e195bfb56fc92e0b8506454f868d8","abstract_canon_sha256":"a3791bb437be33ff574ff16e7dc21c1888cea5663a67798a8e1189fbb171257b"},"schema_version":"1.0"},"canonical_sha256":"ff0ff0e724f4d938882f279a2e435365cc4f98666075b95149b2d3c4d4f7c055","source":{"kind":"arxiv","id":"1601.05633","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1601.05633","created_at":"2026-05-18T00:07:22Z"},{"alias_kind":"arxiv_version","alias_value":"1601.05633v5","created_at":"2026-05-18T00:07:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1601.05633","created_at":"2026-05-18T00:07:22Z"},{"alias_kind":"pith_short_12","alias_value":"74H7BZZE6TMT","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_16","alias_value":"74H7BZZE6TMTRCBP","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_8","alias_value":"74H7BZZE","created_at":"2026-05-18T12:30:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:74H7BZZE6TMTRCBPE6NC4Q2TMX","target":"record","payload":{"canonical_record":{"source":{"id":"1601.05633","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-01-21T13:54:17Z","cross_cats_sorted":[],"title_canon_sha256":"c755a6e8f2e2cd1cc4d9a14559456ba8236e195bfb56fc92e0b8506454f868d8","abstract_canon_sha256":"a3791bb437be33ff574ff16e7dc21c1888cea5663a67798a8e1189fbb171257b"},"schema_version":"1.0"},"canonical_sha256":"ff0ff0e724f4d938882f279a2e435365cc4f98666075b95149b2d3c4d4f7c055","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:07:22.020238Z","signature_b64":"lnkz+vdjAfq+4kwaeVaGEHvJ1SXBdO0pwsRvggA4IXX+ZkfP0uiEzSo1ziXEfl7zf474WrGF1VRvJ240xhPeAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff0ff0e724f4d938882f279a2e435365cc4f98666075b95149b2d3c4d4f7c055","last_reissued_at":"2026-05-18T00:07:22.019604Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:07:22.019604Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1601.05633","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:07:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iYZo2d/wfQHa2r6TDzDGFTt+DIwIlx3cgkRR0Lj+WWWhspzxNF/wNfdkwSKoAY1plDGOyn67fvfWcSfNS7bvAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T01:01:09.637630Z"},"content_sha256":"f27090a7a14934feded1f48be8181f85a8a2754e52a2e1b2328b6dc57c15c11c","schema_version":"1.0","event_id":"sha256:f27090a7a14934feded1f48be8181f85a8a2754e52a2e1b2328b6dc57c15c11c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:74H7BZZE6TMTRCBPE6NC4Q2TMX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Repelling-Attracting Metropolis Algorithm for Multimodality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"David A. van Dyk, Hyungsuk Tak, Xiao-Li Meng","submitted_at":"2016-01-21T13:54:17Z","abstract_excerpt":"Although the Metropolis algorithm is simple to implement, it often has difficulties exploring multimodal distributions. We propose the repelling-attracting Metropolis (RAM) algorithm that maintains the simple-to-implement nature of the Metropolis algorithm, but is more likely to jump between modes. The RAM algorithm is a Metropolis-Hastings algorithm with a proposal that consists of a downhill move in density that aims to make local modes repelling, followed by an uphill move in density that aims to make local modes attracting. The downhill move is achieved via a reciprocal Metropolis ratio so"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1601.05633","kind":"arxiv","version":5},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:07:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SsO1tzi6JBkvi7AXAZ0a/LAabvfeo1vqYYHUevxivnphBL78QwUdOJxoOYTz2blzIQQkVq4s5jxwpCoMp/gdDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T01:01:09.637981Z"},"content_sha256":"a9d0cfd99ccf5a4c11b6d10f14416c71f044b3b98a1954bf832e350cd5f91afd","schema_version":"1.0","event_id":"sha256:a9d0cfd99ccf5a4c11b6d10f14416c71f044b3b98a1954bf832e350cd5f91afd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/74H7BZZE6TMTRCBPE6NC4Q2TMX/bundle.json","state_url":"https://pith.science/pith/74H7BZZE6TMTRCBPE6NC4Q2TMX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/74H7BZZE6TMTRCBPE6NC4Q2TMX/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":"2026-05-31T01:01:09Z","links":{"resolver":"https://pith.science/pith/74H7BZZE6TMTRCBPE6NC4Q2TMX","bundle":"https://pith.science/pith/74H7BZZE6TMTRCBPE6NC4Q2TMX/bundle.json","state":"https://pith.science/pith/74H7BZZE6TMTRCBPE6NC4Q2TMX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/74H7BZZE6TMTRCBPE6NC4Q2TMX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:74H7BZZE6TMTRCBPE6NC4Q2TMX","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":"a3791bb437be33ff574ff16e7dc21c1888cea5663a67798a8e1189fbb171257b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-01-21T13:54:17Z","title_canon_sha256":"c755a6e8f2e2cd1cc4d9a14559456ba8236e195bfb56fc92e0b8506454f868d8"},"schema_version":"1.0","source":{"id":"1601.05633","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1601.05633","created_at":"2026-05-18T00:07:22Z"},{"alias_kind":"arxiv_version","alias_value":"1601.05633v5","created_at":"2026-05-18T00:07:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1601.05633","created_at":"2026-05-18T00:07:22Z"},{"alias_kind":"pith_short_12","alias_value":"74H7BZZE6TMT","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_16","alias_value":"74H7BZZE6TMTRCBP","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_8","alias_value":"74H7BZZE","created_at":"2026-05-18T12:30:04Z"}],"graph_snapshots":[{"event_id":"sha256:a9d0cfd99ccf5a4c11b6d10f14416c71f044b3b98a1954bf832e350cd5f91afd","target":"graph","created_at":"2026-05-18T00:07:22Z","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":"Although the Metropolis algorithm is simple to implement, it often has difficulties exploring multimodal distributions. We propose the repelling-attracting Metropolis (RAM) algorithm that maintains the simple-to-implement nature of the Metropolis algorithm, but is more likely to jump between modes. The RAM algorithm is a Metropolis-Hastings algorithm with a proposal that consists of a downhill move in density that aims to make local modes repelling, followed by an uphill move in density that aims to make local modes attracting. The downhill move is achieved via a reciprocal Metropolis ratio so","authors_text":"David A. van Dyk, Hyungsuk Tak, Xiao-Li Meng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-01-21T13:54:17Z","title":"A Repelling-Attracting Metropolis Algorithm for Multimodality"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1601.05633","kind":"arxiv","version":5},"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:f27090a7a14934feded1f48be8181f85a8a2754e52a2e1b2328b6dc57c15c11c","target":"record","created_at":"2026-05-18T00:07:22Z","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":"a3791bb437be33ff574ff16e7dc21c1888cea5663a67798a8e1189fbb171257b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-01-21T13:54:17Z","title_canon_sha256":"c755a6e8f2e2cd1cc4d9a14559456ba8236e195bfb56fc92e0b8506454f868d8"},"schema_version":"1.0","source":{"id":"1601.05633","kind":"arxiv","version":5}},"canonical_sha256":"ff0ff0e724f4d938882f279a2e435365cc4f98666075b95149b2d3c4d4f7c055","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff0ff0e724f4d938882f279a2e435365cc4f98666075b95149b2d3c4d4f7c055","first_computed_at":"2026-05-18T00:07:22.019604Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:07:22.019604Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lnkz+vdjAfq+4kwaeVaGEHvJ1SXBdO0pwsRvggA4IXX+ZkfP0uiEzSo1ziXEfl7zf474WrGF1VRvJ240xhPeAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:07:22.020238Z","signed_message":"canonical_sha256_bytes"},"source_id":"1601.05633","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f27090a7a14934feded1f48be8181f85a8a2754e52a2e1b2328b6dc57c15c11c","sha256:a9d0cfd99ccf5a4c11b6d10f14416c71f044b3b98a1954bf832e350cd5f91afd"],"state_sha256":"d82fb4c2564856abb847eb50bca809561f7bcbfacea50f2386544c4344111ebc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T6YlSMjgSTPluyIxhSpvaWCLqzfSaN6DiJIkcmjJXWsaHYjfvCk8pcYGEAxG9aoRXzgiNS96CyR0Z+BvuAz0Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T01:01:09.640262Z","bundle_sha256":"65c8c3c5253bab20c8633b956d6c9eb4fb1d98ef6f110a3a9f13757bda5eb361"}}