{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:FAX47J3IV73IYBENA3Q7GMMTMY","short_pith_number":"pith:FAX47J3I","canonical_record":{"source":{"id":"2508.13313","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-18T19:00:45Z","cross_cats_sorted":["cs.LG","math.OC"],"title_canon_sha256":"4347a726ea624b048e3eef9df7d8e514e1d8eacebd5f8f58c4656ae1e2158d85","abstract_canon_sha256":"02b8f90ad6e54c8d6dee16532d0d61bc7ed7b1d0e1957bfd882cbd8ae531557a"},"schema_version":"1.0"},"canonical_sha256":"282fcfa768aff68c048d06e1f3319366074ed241de637629552b7daad22b9c7b","source":{"kind":"arxiv","id":"2508.13313","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.13313","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"arxiv_version","alias_value":"2508.13313v4","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.13313","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"pith_short_12","alias_value":"FAX47J3IV73I","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"pith_short_16","alias_value":"FAX47J3IV73IYBEN","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"pith_short_8","alias_value":"FAX47J3I","created_at":"2026-06-19T16:12:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:FAX47J3IV73IYBENA3Q7GMMTMY","target":"record","payload":{"canonical_record":{"source":{"id":"2508.13313","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-18T19:00:45Z","cross_cats_sorted":["cs.LG","math.OC"],"title_canon_sha256":"4347a726ea624b048e3eef9df7d8e514e1d8eacebd5f8f58c4656ae1e2158d85","abstract_canon_sha256":"02b8f90ad6e54c8d6dee16532d0d61bc7ed7b1d0e1957bfd882cbd8ae531557a"},"schema_version":"1.0"},"canonical_sha256":"282fcfa768aff68c048d06e1f3319366074ed241de637629552b7daad22b9c7b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:12:14.676073Z","signature_b64":"yGxgzk2o3fDHiQygfbI57aHTQAMKMKnPxvFLqNG/+Pv72nhO7ib7fsWgziYude26E0uShSKCaCn8rrn6FvNkAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"282fcfa768aff68c048d06e1f3319366074ed241de637629552b7daad22b9c7b","last_reissued_at":"2026-06-19T16:12:14.675653Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:12:14.675653Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.13313","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-19T16:12:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L5QDRThLlNQPMIe0PHeLzEpxOO+9AYUV6I822B/+D23M15zSoMM7Dcx4vfy1NTljxmVAd688bSbZVLqylTPCDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T06:51:09.167122Z"},"content_sha256":"3a794d5f191daf2c26a13f476ba5a1cd1c6ae148213775da961398f2242ddfd7","schema_version":"1.0","event_id":"sha256:3a794d5f191daf2c26a13f476ba5a1cd1c6ae148213775da961398f2242ddfd7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:FAX47J3IV73IYBENA3Q7GMMTMY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Flow Matching for Efficient and Scalable Data Assimilation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","math.OC"],"primary_cat":"stat.ML","authors_text":"Bao Wang, Bohan Chen, So Takao, Taos Transue","submitted_at":"2025-08-18T19:00:45Z","abstract_excerpt":"Data assimilation (DA) estimates a dynamical system's state from noisy observations. Recent generative models like the ensemble score filter (EnSF) improve DA in high-dimensional nonlinear settings but are computationally expensive. We introduce the ensemble flow filter (EnFF), a training-free, flow matching (FM)-based framework that accelerates sampling and offers flexibility in flow design. EnFF uses Monte Carlo estimators for the marginal flow field, localized guidance for observation assimilation, and utilizes a novel flow path that exploits the Bayesian DA formulation. It generalizes clas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.13313","kind":"arxiv","version":4},"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/2508.13313/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":"2026-06-19T16:12:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pb1+0h+tWuxL+CWaqx0loehARiCF/RQVAZbzDjHsqSzIuvcguyBp5M3C5pOkZWtBtYaPgwUJ0AauuPNA/zwoBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T06:51:09.167523Z"},"content_sha256":"3ce9fc502f8154004dbfad5fec409c78ccc037e95814fb5059a4ac50b6df75ad","schema_version":"1.0","event_id":"sha256:3ce9fc502f8154004dbfad5fec409c78ccc037e95814fb5059a4ac50b6df75ad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FAX47J3IV73IYBENA3Q7GMMTMY/bundle.json","state_url":"https://pith.science/pith/FAX47J3IV73IYBENA3Q7GMMTMY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FAX47J3IV73IYBENA3Q7GMMTMY/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":"2026-07-03T06:51:09Z","links":{"resolver":"https://pith.science/pith/FAX47J3IV73IYBENA3Q7GMMTMY","bundle":"https://pith.science/pith/FAX47J3IV73IYBENA3Q7GMMTMY/bundle.json","state":"https://pith.science/pith/FAX47J3IV73IYBENA3Q7GMMTMY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FAX47J3IV73IYBENA3Q7GMMTMY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FAX47J3IV73IYBENA3Q7GMMTMY","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":"02b8f90ad6e54c8d6dee16532d0d61bc7ed7b1d0e1957bfd882cbd8ae531557a","cross_cats_sorted":["cs.LG","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-18T19:00:45Z","title_canon_sha256":"4347a726ea624b048e3eef9df7d8e514e1d8eacebd5f8f58c4656ae1e2158d85"},"schema_version":"1.0","source":{"id":"2508.13313","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.13313","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"arxiv_version","alias_value":"2508.13313v4","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.13313","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"pith_short_12","alias_value":"FAX47J3IV73I","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"pith_short_16","alias_value":"FAX47J3IV73IYBEN","created_at":"2026-06-19T16:12:14Z"},{"alias_kind":"pith_short_8","alias_value":"FAX47J3I","created_at":"2026-06-19T16:12:14Z"}],"graph_snapshots":[{"event_id":"sha256:3ce9fc502f8154004dbfad5fec409c78ccc037e95814fb5059a4ac50b6df75ad","target":"graph","created_at":"2026-06-19T16:12:14Z","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/2508.13313/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data assimilation (DA) estimates a dynamical system's state from noisy observations. Recent generative models like the ensemble score filter (EnSF) improve DA in high-dimensional nonlinear settings but are computationally expensive. We introduce the ensemble flow filter (EnFF), a training-free, flow matching (FM)-based framework that accelerates sampling and offers flexibility in flow design. EnFF uses Monte Carlo estimators for the marginal flow field, localized guidance for observation assimilation, and utilizes a novel flow path that exploits the Bayesian DA formulation. It generalizes clas","authors_text":"Bao Wang, Bohan Chen, So Takao, Taos Transue","cross_cats":["cs.LG","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-18T19:00:45Z","title":"Flow Matching for Efficient and Scalable Data Assimilation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.13313","kind":"arxiv","version":4},"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":"sha256:3a794d5f191daf2c26a13f476ba5a1cd1c6ae148213775da961398f2242ddfd7","target":"record","created_at":"2026-06-19T16:12:14Z","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":"02b8f90ad6e54c8d6dee16532d0d61bc7ed7b1d0e1957bfd882cbd8ae531557a","cross_cats_sorted":["cs.LG","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-18T19:00:45Z","title_canon_sha256":"4347a726ea624b048e3eef9df7d8e514e1d8eacebd5f8f58c4656ae1e2158d85"},"schema_version":"1.0","source":{"id":"2508.13313","kind":"arxiv","version":4}},"canonical_sha256":"282fcfa768aff68c048d06e1f3319366074ed241de637629552b7daad22b9c7b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"282fcfa768aff68c048d06e1f3319366074ed241de637629552b7daad22b9c7b","first_computed_at":"2026-06-19T16:12:14.675653Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:12:14.675653Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yGxgzk2o3fDHiQygfbI57aHTQAMKMKnPxvFLqNG/+Pv72nhO7ib7fsWgziYude26E0uShSKCaCn8rrn6FvNkAA==","signature_status":"signed_v1","signed_at":"2026-06-19T16:12:14.676073Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.13313","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3a794d5f191daf2c26a13f476ba5a1cd1c6ae148213775da961398f2242ddfd7","sha256:3ce9fc502f8154004dbfad5fec409c78ccc037e95814fb5059a4ac50b6df75ad"],"state_sha256":"cd34d16a13aa07ad0827d81feac57a0ed42dee797d7638b2e048af3d07d811dd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zPanABTUSFeEpWeM7y5124gBnZzq+OFKxyNu0iR4nFElXwzwPY2lpObpA3o0PJNFU/ysxIllCRw6NjGIeM6WCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-03T06:51:09.169732Z","bundle_sha256":"0ccbdeadf2c55316c5237204a88d8d3ebd85dc44f9d3107bcd476c6ed21bda73"}}