{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:B2FISPAU7DDGPKAXXN5CRPRIW6","short_pith_number":"pith:B2FISPAU","schema_version":"1.0","canonical_sha256":"0e8a893c14f8c667a817bb7a28be28b7a5e6152f8915ef8f367ec749d0661588","source":{"kind":"arxiv","id":"2602.16634","version":2},"attestation_state":"computed","paper":{"title":"Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","physics.bio-ph","physics.chem-ph"],"primary_cat":"stat.ML","authors_text":"Adam E. Foster, Cecilia Clementi, Christopher M. Bishop, Frank No\\'e, Iryna Zaporozhets, Jos\\'e Jim\\'enez Luna, Lixin Sun, Ludwig Winkler, Michael Gastegger, Sarah Lewis, Tim Hempel, Yaoyi Chen, Yu Xie","submitted_at":"2026-02-18T17:26:15Z","abstract_excerpt":"The rare-event sampling problem has long been the central limiting factor in molecular dynamics (MD), especially in biomolecular simulation. Recently, diffusion models such as BioEmu have emerged as powerful equilibrium samplers that generate independent samples from complex molecular distributions, eliminating the cost of sampling rare transition events. However, a sampling problem remains when computing observables that rely on states which are rare in equilibrium, for example folding free energies. Here, we introduce enhanced diffusion sampling, enabling efficient exploration of rare-event "},"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":"2602.16634","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2026-02-18T17:26:15Z","cross_cats_sorted":["cs.AI","cs.LG","physics.bio-ph","physics.chem-ph"],"title_canon_sha256":"8ada6c604759ce56c270fa0c1db2472b2b35b5fa1b91291378f2cf140d50c43b","abstract_canon_sha256":"83b66ff8fc39f85957c6b9206640b31ec5ed2462238a7f9c4581926f2f7d4179"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T01:17:34.354724Z","signature_b64":"XE1/wQB2CxSJauudTH6It1HyOMhJjQSSrzNRxJbcWgcL6FTmC//P0yW7C+cuzNK2RKOJUCOQ94Ixxl+QcNEDDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0e8a893c14f8c667a817bb7a28be28b7a5e6152f8915ef8f367ec749d0661588","last_reissued_at":"2026-06-30T01:17:34.354080Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T01:17:34.354080Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","physics.bio-ph","physics.chem-ph"],"primary_cat":"stat.ML","authors_text":"Adam E. Foster, Cecilia Clementi, Christopher M. Bishop, Frank No\\'e, Iryna Zaporozhets, Jos\\'e Jim\\'enez Luna, Lixin Sun, Ludwig Winkler, Michael Gastegger, Sarah Lewis, Tim Hempel, Yaoyi Chen, Yu Xie","submitted_at":"2026-02-18T17:26:15Z","abstract_excerpt":"The rare-event sampling problem has long been the central limiting factor in molecular dynamics (MD), especially in biomolecular simulation. Recently, diffusion models such as BioEmu have emerged as powerful equilibrium samplers that generate independent samples from complex molecular distributions, eliminating the cost of sampling rare transition events. However, a sampling problem remains when computing observables that rely on states which are rare in equilibrium, for example folding free energies. Here, we introduce enhanced diffusion sampling, enabling efficient exploration of rare-event "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.16634","kind":"arxiv","version":2},"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/2602.16634/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2602.16634","created_at":"2026-06-30T01:17:34.354156+00:00"},{"alias_kind":"arxiv_version","alias_value":"2602.16634v2","created_at":"2026-06-30T01:17:34.354156+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.16634","created_at":"2026-06-30T01:17:34.354156+00:00"},{"alias_kind":"pith_short_12","alias_value":"B2FISPAU7DDG","created_at":"2026-06-30T01:17:34.354156+00:00"},{"alias_kind":"pith_short_16","alias_value":"B2FISPAU7DDGPKAX","created_at":"2026-06-30T01:17:34.354156+00:00"},{"alias_kind":"pith_short_8","alias_value":"B2FISPAU","created_at":"2026-06-30T01:17:34.354156+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":4,"internal_anchor_count":4,"sample":[{"citing_arxiv_id":"2606.30687","citing_title":"Unsupervised Thermodynamics of Molecular Diffusion Models: Action-Operator Semantics and Auditable Free-Energy Readout","ref_index":8,"is_internal_anchor":true},{"citing_arxiv_id":"2606.29110","citing_title":"Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps","ref_index":22,"is_internal_anchor":true},{"citing_arxiv_id":"2605.19050","citing_title":"Generative Pseudo-Force Fields for Molecular Generation","ref_index":78,"is_internal_anchor":true},{"citing_arxiv_id":"2604.09769","citing_title":"Differentiable free energy surface: a variational approach to directly observing rare events using generative deep-learning models","ref_index":35,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6","json":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6.json","graph_json":"https://pith.science/api/pith-number/B2FISPAU7DDGPKAXXN5CRPRIW6/graph.json","events_json":"https://pith.science/api/pith-number/B2FISPAU7DDGPKAXXN5CRPRIW6/events.json","paper":"https://pith.science/paper/B2FISPAU"},"agent_actions":{"view_html":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6","download_json":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6.json","view_paper":"https://pith.science/paper/B2FISPAU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2602.16634&json=true","fetch_graph":"https://pith.science/api/pith-number/B2FISPAU7DDGPKAXXN5CRPRIW6/graph.json","fetch_events":"https://pith.science/api/pith-number/B2FISPAU7DDGPKAXXN5CRPRIW6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6/action/storage_attestation","attest_author":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6/action/author_attestation","sign_citation":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6/action/citation_signature","submit_replication":"https://pith.science/pith/B2FISPAU7DDGPKAXXN5CRPRIW6/action/replication_record"}},"created_at":"2026-06-30T01:17:34.354156+00:00","updated_at":"2026-06-30T01:17:34.354156+00:00"}