{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4HB2PFYTI6HSMCMTXD7APRN3TI","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":"b2526e7108740e9121d7ffc46404348a49769fe45055f74273b0e9e53fc28d3c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2025-03-03T16:20:19Z","title_canon_sha256":"24a8824ca65abeb476f440d587705318da978274bcadc10b8aac3e7ba250c18a"},"schema_version":"1.0","source":{"id":"2503.01707","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.01707","created_at":"2026-07-05T11:04:46Z"},{"alias_kind":"arxiv_version","alias_value":"2503.01707v2","created_at":"2026-07-05T11:04:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.01707","created_at":"2026-07-05T11:04:46Z"},{"alias_kind":"pith_short_12","alias_value":"4HB2PFYTI6HS","created_at":"2026-07-05T11:04:46Z"},{"alias_kind":"pith_short_16","alias_value":"4HB2PFYTI6HSMCMT","created_at":"2026-07-05T11:04:46Z"},{"alias_kind":"pith_short_8","alias_value":"4HB2PFYT","created_at":"2026-07-05T11:04:46Z"}],"graph_snapshots":[{"event_id":"sha256:995b5c7314350e7d3f837d146e385f7dffc173c7761bbefcac7d9e51f87bcac1","target":"graph","created_at":"2026-07-05T11:04:46Z","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/2503.01707/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sampling from high dimensional distributions is a computational bottleneck in many scientific applications. Hamiltonian Monte Carlo (HMC), and in particular the No-U-Turn Sampler (NUTS), are widely used, yet they struggle on problems with a very large number of parameters or a complicated geometry. Microcanonical Langevin Monte Carlo (MCLMC) has been recently proposed as an alternative which shows striking gains in efficiency over NUTS, especially for high-dimensional problems. However, it produces biased samples, with a bias that is hard to control in general. We introduce the Metropolis-Adju","authors_text":"Jakob Robnik, Reuben Cohn-Gordon, Uro\\v{s} Seljak","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2025-03-03T16:20:19Z","title":"Metropolis Adjusted Microcanonical Hamiltonian Monte Carlo"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.01707","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":"sha256:0a486bdf53490aabee5beb0b924b032e936616cdadfdb3cfb4f8ae5273c503a8","target":"record","created_at":"2026-07-05T11:04:46Z","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":"b2526e7108740e9121d7ffc46404348a49769fe45055f74273b0e9e53fc28d3c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2025-03-03T16:20:19Z","title_canon_sha256":"24a8824ca65abeb476f440d587705318da978274bcadc10b8aac3e7ba250c18a"},"schema_version":"1.0","source":{"id":"2503.01707","kind":"arxiv","version":2}},"canonical_sha256":"e1c3a79713478f260993b8fe07c5bb9a2fa2f952a31e3da4c81ac6fc420e9bfe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e1c3a79713478f260993b8fe07c5bb9a2fa2f952a31e3da4c81ac6fc420e9bfe","first_computed_at":"2026-07-05T11:04:46.749591Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:04:46.749591Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"b9xzgNJ8n76+eNv5dRMonha9+ota4PycWnL0oISqvzDAjmnnVGXOsmzBULagHb8OepD+s1gn8F84KWyp5DRZDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:04:46.750049Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.01707","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0a486bdf53490aabee5beb0b924b032e936616cdadfdb3cfb4f8ae5273c503a8","sha256:995b5c7314350e7d3f837d146e385f7dffc173c7761bbefcac7d9e51f87bcac1"],"state_sha256":"1df167f28fe207a936f8be407323e806ebca65b7a290bf9e5863b776826a9377"}