{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:4BEE73SYUXFLKVNSKPB3BEK5DV","short_pith_number":"pith:4BEE73SY","canonical_record":{"source":{"id":"2308.16073","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.ao-ph","submitted_at":"2023-08-30T14:50:49Z","cross_cats_sorted":[],"title_canon_sha256":"8b0711065c8c02a22716b0924a2d613fc3b04c3e212761d411d38a8fef58b158","abstract_canon_sha256":"5c9e8c26bf9d9ba6aa3d7dfb34699652d9fb2ef39a8142db6d6c5b654b2e9f2c"},"schema_version":"1.0"},"canonical_sha256":"e0484fee58a5cab555b253c3b0915d1d6cc398d5c059d8f047df5d92d977d500","source":{"kind":"arxiv","id":"2308.16073","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.16073","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"arxiv_version","alias_value":"2308.16073v3","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.16073","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"pith_short_12","alias_value":"4BEE73SYUXFL","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"pith_short_16","alias_value":"4BEE73SYUXFLKVNS","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"pith_short_8","alias_value":"4BEE73SY","created_at":"2026-07-05T08:12:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:4BEE73SYUXFLKVNSKPB3BEK5DV","target":"record","payload":{"canonical_record":{"source":{"id":"2308.16073","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.ao-ph","submitted_at":"2023-08-30T14:50:49Z","cross_cats_sorted":[],"title_canon_sha256":"8b0711065c8c02a22716b0924a2d613fc3b04c3e212761d411d38a8fef58b158","abstract_canon_sha256":"5c9e8c26bf9d9ba6aa3d7dfb34699652d9fb2ef39a8142db6d6c5b654b2e9f2c"},"schema_version":"1.0"},"canonical_sha256":"e0484fee58a5cab555b253c3b0915d1d6cc398d5c059d8f047df5d92d977d500","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:12:27.191747Z","signature_b64":"zfZTwlRLcwY7zTlUOX61HFSJNMh42QhDzvy0gTUcsUwmjia3CpMEVXOekRQehDLn+zTsPmaKpFP8/KlJd63PBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e0484fee58a5cab555b253c3b0915d1d6cc398d5c059d8f047df5d92d977d500","last_reissued_at":"2026-07-05T08:12:27.191270Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:12:27.191270Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.16073","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:12:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bJG9rNztWRpiwc3zSZrtOM/PRjHdpwIxs3MH+8B1NZdbbcONf3J17gcpBFn94lBYgcFjVSEV5vMFd7F8a2S8Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T20:51:19.088045Z"},"content_sha256":"3d67ce96a70cd2738bc503f576f15481af3bb95f7725468da8b89df885f3f86d","schema_version":"1.0","event_id":"sha256:3d67ce96a70cd2738bc503f576f15481af3bb95f7725468da8b89df885f3f86d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:4BEE73SYUXFLKVNSKPB3BEK5DV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"3D-Var Data Assimilation using a Variational Autoencoder","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.ao-ph","authors_text":"Bo\\v{s}tjan Melinc, \\v{Z}iga Zaplotnik","submitted_at":"2023-08-30T14:50:49Z","abstract_excerpt":"Data assimilation of atmospheric observations traditionally relies on variational and Kalman filter methods. Here, an alternative neural-network data assimilation (NNDA) with variational autoencoder (VAE) is proposed. The three-dimensional variational (3D-Var) data assimilation cost function is utilised to determine the analysis that optimally fuses simulated observations and the encoded short-range persistence forecast (background), accounting for their errors. The minimisation is performed in the reduced-order latent space, discovered by the VAE. The variational problem is auto-differentiabl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.16073","kind":"arxiv","version":3},"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/2308.16073/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":"2026-07-05T08:12:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n9yC9f4cUMs3lRqBJigRWxFumuPJK9FJRyMtdf0ZktL3FN8gK/VbxYx5TYpTSdwzVo2EUKXx8AYASc0VUudbCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T20:51:19.088888Z"},"content_sha256":"4140e25c83934c7f92ed1671006b0cc6a618d392d10f188c8528e4ab82c9f4c7","schema_version":"1.0","event_id":"sha256:4140e25c83934c7f92ed1671006b0cc6a618d392d10f188c8528e4ab82c9f4c7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4BEE73SYUXFLKVNSKPB3BEK5DV/bundle.json","state_url":"https://pith.science/pith/4BEE73SYUXFLKVNSKPB3BEK5DV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4BEE73SYUXFLKVNSKPB3BEK5DV/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":"2026-08-11T20:51:19Z","links":{"resolver":"https://pith.science/pith/4BEE73SYUXFLKVNSKPB3BEK5DV","bundle":"https://pith.science/pith/4BEE73SYUXFLKVNSKPB3BEK5DV/bundle.json","state":"https://pith.science/pith/4BEE73SYUXFLKVNSKPB3BEK5DV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4BEE73SYUXFLKVNSKPB3BEK5DV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:4BEE73SYUXFLKVNSKPB3BEK5DV","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":"5c9e8c26bf9d9ba6aa3d7dfb34699652d9fb2ef39a8142db6d6c5b654b2e9f2c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.ao-ph","submitted_at":"2023-08-30T14:50:49Z","title_canon_sha256":"8b0711065c8c02a22716b0924a2d613fc3b04c3e212761d411d38a8fef58b158"},"schema_version":"1.0","source":{"id":"2308.16073","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.16073","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"arxiv_version","alias_value":"2308.16073v3","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.16073","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"pith_short_12","alias_value":"4BEE73SYUXFL","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"pith_short_16","alias_value":"4BEE73SYUXFLKVNS","created_at":"2026-07-05T08:12:27Z"},{"alias_kind":"pith_short_8","alias_value":"4BEE73SY","created_at":"2026-07-05T08:12:27Z"}],"graph_snapshots":[{"event_id":"sha256:4140e25c83934c7f92ed1671006b0cc6a618d392d10f188c8528e4ab82c9f4c7","target":"graph","created_at":"2026-07-05T08:12:27Z","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/2308.16073/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data assimilation of atmospheric observations traditionally relies on variational and Kalman filter methods. Here, an alternative neural-network data assimilation (NNDA) with variational autoencoder (VAE) is proposed. The three-dimensional variational (3D-Var) data assimilation cost function is utilised to determine the analysis that optimally fuses simulated observations and the encoded short-range persistence forecast (background), accounting for their errors. The minimisation is performed in the reduced-order latent space, discovered by the VAE. The variational problem is auto-differentiabl","authors_text":"Bo\\v{s}tjan Melinc, \\v{Z}iga Zaplotnik","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.ao-ph","submitted_at":"2023-08-30T14:50:49Z","title":"3D-Var Data Assimilation using a Variational Autoencoder"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.16073","kind":"arxiv","version":3},"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":"sha256:3d67ce96a70cd2738bc503f576f15481af3bb95f7725468da8b89df885f3f86d","target":"record","created_at":"2026-07-05T08:12:27Z","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":"5c9e8c26bf9d9ba6aa3d7dfb34699652d9fb2ef39a8142db6d6c5b654b2e9f2c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.ao-ph","submitted_at":"2023-08-30T14:50:49Z","title_canon_sha256":"8b0711065c8c02a22716b0924a2d613fc3b04c3e212761d411d38a8fef58b158"},"schema_version":"1.0","source":{"id":"2308.16073","kind":"arxiv","version":3}},"canonical_sha256":"e0484fee58a5cab555b253c3b0915d1d6cc398d5c059d8f047df5d92d977d500","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0484fee58a5cab555b253c3b0915d1d6cc398d5c059d8f047df5d92d977d500","first_computed_at":"2026-07-05T08:12:27.191270Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:12:27.191270Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zfZTwlRLcwY7zTlUOX61HFSJNMh42QhDzvy0gTUcsUwmjia3CpMEVXOekRQehDLn+zTsPmaKpFP8/KlJd63PBw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:12:27.191747Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.16073","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d67ce96a70cd2738bc503f576f15481af3bb95f7725468da8b89df885f3f86d","sha256:4140e25c83934c7f92ed1671006b0cc6a618d392d10f188c8528e4ab82c9f4c7"],"state_sha256":"221ae8f841ffa8077623467cbbdd8377e0dd3503299f0690de030bf20fd4e5a4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x9VEHQNuyOSAXRkvOL6WCWw8idFicuSk52WUZDhBCRIEH75ahndv5MCaqzM6iTXOmExzhDhR1CBA88UWuMCkCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T20:51:19.096236Z","bundle_sha256":"06ff6dcc7db7a4bcf6338e7dcfc4c9987705ad9ee19934bd54b41ff72060d4ce"}}