{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:R2LRCYXXOBQGHJP3AQ42IZBKLJ","short_pith_number":"pith:R2LRCYXX","schema_version":"1.0","canonical_sha256":"8e971162f7706063a5fb0439a4642a5a67a1d43f079123a58b36cc0bbf0ec713","source":{"kind":"arxiv","id":"1604.00889","version":1},"attestation_state":"computed","paper":{"title":"Variable length trajectory compressible hybrid Monte Carlo","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"physics.comp-ph","authors_text":"Akihiko Nishimura, David Dunson","submitted_at":"2016-04-04T14:56:50Z","abstract_excerpt":"Hybrid Monte Carlo (HMC) generates samples from a prescribed probability distribution in a configuration space by simulating Hamiltonian dynamics, followed by the Metropolis (-Hastings) acceptance/rejection step. Compressible HMC (CHMC) generalizes HMC to a situation in which the dynamics is reversible but not necessarily Hamiltonian. This article presents a framework to further extend the algorithm. Within the existing framework, each trajectory of the dynamics must be integrated for the same amount of (random) time to generate a valid Metropolis proposal. Our generalized acceptance/rejection"},"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":"1604.00889","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.comp-ph","submitted_at":"2016-04-04T14:56:50Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"cd7d2920d46a497bef8dbdb25761cc1d95e4ed093f4f3e143a6296e370024695","abstract_canon_sha256":"9067b03cbe8c4ae3cde2ed8170ddf891e475109b92f5c1e6389d05a20b858f22"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:17:47.898343Z","signature_b64":"SwnKRwJ+Jryvk6CH6s1V+4EB6UO3GKNKjKDx6806lrA6mypZhbZiozIfAhBTYeZSsPmESN/WBjIRVBCeAnj1Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e971162f7706063a5fb0439a4642a5a67a1d43f079123a58b36cc0bbf0ec713","last_reissued_at":"2026-05-18T01:17:47.897305Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:17:47.897305Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Variable length trajectory compressible hybrid Monte Carlo","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"physics.comp-ph","authors_text":"Akihiko Nishimura, David Dunson","submitted_at":"2016-04-04T14:56:50Z","abstract_excerpt":"Hybrid Monte Carlo (HMC) generates samples from a prescribed probability distribution in a configuration space by simulating Hamiltonian dynamics, followed by the Metropolis (-Hastings) acceptance/rejection step. Compressible HMC (CHMC) generalizes HMC to a situation in which the dynamics is reversible but not necessarily Hamiltonian. This article presents a framework to further extend the algorithm. Within the existing framework, each trajectory of the dynamics must be integrated for the same amount of (random) time to generate a valid Metropolis proposal. Our generalized acceptance/rejection"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.00889","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":""},"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":"1604.00889","created_at":"2026-05-18T01:17:47.897429+00:00"},{"alias_kind":"arxiv_version","alias_value":"1604.00889v1","created_at":"2026-05-18T01:17:47.897429+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.00889","created_at":"2026-05-18T01:17:47.897429+00:00"},{"alias_kind":"pith_short_12","alias_value":"R2LRCYXXOBQG","created_at":"2026-05-18T12:30:41.710351+00:00"},{"alias_kind":"pith_short_16","alias_value":"R2LRCYXXOBQGHJP3","created_at":"2026-05-18T12:30:41.710351+00:00"},{"alias_kind":"pith_short_8","alias_value":"R2LRCYXX","created_at":"2026-05-18T12:30:41.710351+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/R2LRCYXXOBQGHJP3AQ42IZBKLJ","json":"https://pith.science/pith/R2LRCYXXOBQGHJP3AQ42IZBKLJ.json","graph_json":"https://pith.science/api/pith-number/R2LRCYXXOBQGHJP3AQ42IZBKLJ/graph.json","events_json":"https://pith.science/api/pith-number/R2LRCYXXOBQGHJP3AQ42IZBKLJ/events.json","paper":"https://pith.science/paper/R2LRCYXX"},"agent_actions":{"view_html":"https://pith.science/pith/R2LRCYXXOBQGHJP3AQ42IZBKLJ","download_json":"https://pith.science/pith/R2LRCYXXOBQGHJP3AQ42IZBKLJ.json","view_paper":"https://pith.science/paper/R2LRCYXX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1604.00889&json=true","fetch_graph":"https://pith.science/api/pith-number/R2LRCYXXOBQGHJP3AQ42IZBKLJ/graph.json","fetch_events":"https://pith.science/api/pith-number/R2LRCYXXOBQGHJP3AQ42IZBKLJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/R2LRCYXXOBQGHJP3AQ42IZBKLJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/R2LRCYXXOBQGHJP3AQ42IZBKLJ/action/storage_attestation","attest_author":"https://pith.science/pith/R2LRCYXXOBQGHJP3AQ42IZBKLJ/action/author_attestation","sign_citation":"https://pith.science/pith/R2LRCYXXOBQGHJP3AQ42IZBKLJ/action/citation_signature","submit_replication":"https://pith.science/pith/R2LRCYXXOBQGHJP3AQ42IZBKLJ/action/replication_record"}},"created_at":"2026-05-18T01:17:47.897429+00:00","updated_at":"2026-05-18T01:17:47.897429+00:00"}