{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:J7ARNMN3TDPWTRMXPPFTW434HR","short_pith_number":"pith:J7ARNMN3","canonical_record":{"source":{"id":"2404.00844","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math-ph","submitted_at":"2024-04-01T01:02:34Z","cross_cats_sorted":["math.MP"],"title_canon_sha256":"2a32cbe11296dba56b1be5fcb03c6b12963838e5bbc63bab78598f2401a47808","abstract_canon_sha256":"45a01cbf144c60d65346a0bb61c428a01b89ddb060b3bbcb3dc18e67454597db"},"schema_version":"1.0"},"canonical_sha256":"4fc116b1bb98df69c5977bcb3b737c3c6ea7a839ea2c89e94347314c93d23949","source":{"kind":"arxiv","id":"2404.00844","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.00844","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"arxiv_version","alias_value":"2404.00844v1","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.00844","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"pith_short_12","alias_value":"J7ARNMN3TDPW","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"pith_short_16","alias_value":"J7ARNMN3TDPWTRMX","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"pith_short_8","alias_value":"J7ARNMN3","created_at":"2026-07-05T08:02:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:J7ARNMN3TDPWTRMXPPFTW434HR","target":"record","payload":{"canonical_record":{"source":{"id":"2404.00844","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math-ph","submitted_at":"2024-04-01T01:02:34Z","cross_cats_sorted":["math.MP"],"title_canon_sha256":"2a32cbe11296dba56b1be5fcb03c6b12963838e5bbc63bab78598f2401a47808","abstract_canon_sha256":"45a01cbf144c60d65346a0bb61c428a01b89ddb060b3bbcb3dc18e67454597db"},"schema_version":"1.0"},"canonical_sha256":"4fc116b1bb98df69c5977bcb3b737c3c6ea7a839ea2c89e94347314c93d23949","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:02:57.339336Z","signature_b64":"Ij8mD3MKwwphFBc2cHmyXaOhLlNO0dgEfe5dkiMmAX9lSHk839BVa5SzE5h/M7/0ok7j/5BaHjtnV10Hvt1hDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4fc116b1bb98df69c5977bcb3b737c3c6ea7a839ea2c89e94347314c93d23949","last_reissued_at":"2026-07-05T08:02:57.338848Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:02:57.338848Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.00844","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:02:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mA6EHdDHCCOvmc4q/Xderqzun3AxrXja3Z38E//sahkbUGZni7Pm6GhsLdU9bMIO7iuZdyd4dubnh5gEqSg2CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:04:24.373737Z"},"content_sha256":"3d915118f58e73da4223736f9099cc792a2ec1f00110cef0c55a8e103928c625","schema_version":"1.0","event_id":"sha256:3d915118f58e73da4223736f9099cc792a2ec1f00110cef0c55a8e103928c625"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:J7ARNMN3TDPWTRMXPPFTW434HR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Nonlinear ensemble filtering with diffusion models: Application to the surface quasi-geostrophic dynamics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.MP"],"primary_cat":"math-ph","authors_text":"Feng Bao, Guannan Zhang, Hristo G. Chipilski, Jeffrey S.Whitaker, Siming Liang","submitted_at":"2024-04-01T01:02:34Z","abstract_excerpt":"The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed \\textit{Ensemble Score Filter (EnSF)} is completely training-free and can efficiently generate a set of analysis ensemble members. In this study, we apply the EnSF to a surface quasi-geostrophic model and compare its performance again"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.00844","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2404.00844/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":"2026-07-05T08:02:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MbpgNAlsoRTJuVDlJxhpFRjgl2OO/vp5Tqc+3LooZebOd/IrR2kiJcPModiUCxjUslkca51RG81yfO4goN5lCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:04:24.374276Z"},"content_sha256":"d71da5c94af1842298d7d55b795190161891dc916b83c80534ea88af4711cfbc","schema_version":"1.0","event_id":"sha256:d71da5c94af1842298d7d55b795190161891dc916b83c80534ea88af4711cfbc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J7ARNMN3TDPWTRMXPPFTW434HR/bundle.json","state_url":"https://pith.science/pith/J7ARNMN3TDPWTRMXPPFTW434HR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J7ARNMN3TDPWTRMXPPFTW434HR/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":"2026-08-04T15:04:24Z","links":{"resolver":"https://pith.science/pith/J7ARNMN3TDPWTRMXPPFTW434HR","bundle":"https://pith.science/pith/J7ARNMN3TDPWTRMXPPFTW434HR/bundle.json","state":"https://pith.science/pith/J7ARNMN3TDPWTRMXPPFTW434HR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J7ARNMN3TDPWTRMXPPFTW434HR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:J7ARNMN3TDPWTRMXPPFTW434HR","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":"45a01cbf144c60d65346a0bb61c428a01b89ddb060b3bbcb3dc18e67454597db","cross_cats_sorted":["math.MP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math-ph","submitted_at":"2024-04-01T01:02:34Z","title_canon_sha256":"2a32cbe11296dba56b1be5fcb03c6b12963838e5bbc63bab78598f2401a47808"},"schema_version":"1.0","source":{"id":"2404.00844","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.00844","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"arxiv_version","alias_value":"2404.00844v1","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.00844","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"pith_short_12","alias_value":"J7ARNMN3TDPW","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"pith_short_16","alias_value":"J7ARNMN3TDPWTRMX","created_at":"2026-07-05T08:02:57Z"},{"alias_kind":"pith_short_8","alias_value":"J7ARNMN3","created_at":"2026-07-05T08:02:57Z"}],"graph_snapshots":[{"event_id":"sha256:d71da5c94af1842298d7d55b795190161891dc916b83c80534ea88af4711cfbc","target":"graph","created_at":"2026-07-05T08:02:57Z","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/2404.00844/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed \\textit{Ensemble Score Filter (EnSF)} is completely training-free and can efficiently generate a set of analysis ensemble members. In this study, we apply the EnSF to a surface quasi-geostrophic model and compare its performance again","authors_text":"Feng Bao, Guannan Zhang, Hristo G. Chipilski, Jeffrey S.Whitaker, Siming Liang","cross_cats":["math.MP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math-ph","submitted_at":"2024-04-01T01:02:34Z","title":"Nonlinear ensemble filtering with diffusion models: Application to the surface quasi-geostrophic dynamics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.00844","kind":"arxiv","version":1},"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":"sha256:3d915118f58e73da4223736f9099cc792a2ec1f00110cef0c55a8e103928c625","target":"record","created_at":"2026-07-05T08:02:57Z","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":"45a01cbf144c60d65346a0bb61c428a01b89ddb060b3bbcb3dc18e67454597db","cross_cats_sorted":["math.MP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math-ph","submitted_at":"2024-04-01T01:02:34Z","title_canon_sha256":"2a32cbe11296dba56b1be5fcb03c6b12963838e5bbc63bab78598f2401a47808"},"schema_version":"1.0","source":{"id":"2404.00844","kind":"arxiv","version":1}},"canonical_sha256":"4fc116b1bb98df69c5977bcb3b737c3c6ea7a839ea2c89e94347314c93d23949","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4fc116b1bb98df69c5977bcb3b737c3c6ea7a839ea2c89e94347314c93d23949","first_computed_at":"2026-07-05T08:02:57.338848Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:02:57.338848Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ij8mD3MKwwphFBc2cHmyXaOhLlNO0dgEfe5dkiMmAX9lSHk839BVa5SzE5h/M7/0ok7j/5BaHjtnV10Hvt1hDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:02:57.339336Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.00844","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d915118f58e73da4223736f9099cc792a2ec1f00110cef0c55a8e103928c625","sha256:d71da5c94af1842298d7d55b795190161891dc916b83c80534ea88af4711cfbc"],"state_sha256":"96096984afd9e4eff3a130a2458a0db8b65b0bfa9e57983d96c9d72c956aa73a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zGZHGgtChq8kVL1vFaQ68ilGKSqMnEcDppsFbdFsH+njTvzUnXtwtVzFXO6mRH2uEaTLamFNHC7703QYCHqNAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T15:04:24.380484Z","bundle_sha256":"dab2c32438deb5d9826c39e6fef4cd8747af741dc31cbecbe91fade9b899a63c"}}