{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:6AREZ7KWSJU6QDBM5KU53GTCDG","short_pith_number":"pith:6AREZ7KW","schema_version":"1.0","canonical_sha256":"f0224cfd569269e80c2ceaa9dd9a6219b5ed509247b9b62a478b766c40f59c8a","source":{"kind":"arxiv","id":"1207.0454","version":1},"attestation_state":"computed","paper":{"title":"Non-Smooth Variational Data Assimilation with Sparse Priors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.geo-ph"],"primary_cat":"physics.data-an","authors_text":"Ardeshir M. Ebtehaj, Arthur Y. Hou, Efi Foufoula-Georgiou, Sara Q. Zhang","submitted_at":"2012-07-02T17:50:11Z","abstract_excerpt":"This paper proposes an extension to the classical 3D variational data assimilation approach by explicitly incorporating as a prior information, the transform-domain sparsity observed in a large class of geophysical signals. In particular, the proposed framework extends the maximum likelihood estimation of the analysis state to the maximum a posteriori estimator, from a Bayesian perspective. The promise of the methodology is demonstrated via application to a 1D synthetic example."},"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":"1207.0454","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.data-an","submitted_at":"2012-07-02T17:50:11Z","cross_cats_sorted":["physics.geo-ph"],"title_canon_sha256":"85fe7ab57aee2419ebdfe0ef9e04e6998e501b5ae9f9f2f5dcda120ecda4d26d","abstract_canon_sha256":"1f7b7749b5f715ddc8ab926f3ce4babb244a2933bd84a3dfeda32ffac2524b15"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:51:59.298284Z","signature_b64":"4dnVeXsDW++RQtQIvl4gftUwAkienW8KnTAcl3R48oEcs+Mo62/1cUmSN+C1yQbsJwg+yR6UIeXwBYKeiIZiDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f0224cfd569269e80c2ceaa9dd9a6219b5ed509247b9b62a478b766c40f59c8a","last_reissued_at":"2026-05-18T03:51:59.297623Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:51:59.297623Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Non-Smooth Variational Data Assimilation with Sparse Priors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.geo-ph"],"primary_cat":"physics.data-an","authors_text":"Ardeshir M. Ebtehaj, Arthur Y. Hou, Efi Foufoula-Georgiou, Sara Q. Zhang","submitted_at":"2012-07-02T17:50:11Z","abstract_excerpt":"This paper proposes an extension to the classical 3D variational data assimilation approach by explicitly incorporating as a prior information, the transform-domain sparsity observed in a large class of geophysical signals. In particular, the proposed framework extends the maximum likelihood estimation of the analysis state to the maximum a posteriori estimator, from a Bayesian perspective. The promise of the methodology is demonstrated via application to a 1D synthetic example."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1207.0454","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":""},"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":"1207.0454","created_at":"2026-05-18T03:51:59.297731+00:00"},{"alias_kind":"arxiv_version","alias_value":"1207.0454v1","created_at":"2026-05-18T03:51:59.297731+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1207.0454","created_at":"2026-05-18T03:51:59.297731+00:00"},{"alias_kind":"pith_short_12","alias_value":"6AREZ7KWSJU6","created_at":"2026-05-18T12:26:56.085431+00:00"},{"alias_kind":"pith_short_16","alias_value":"6AREZ7KWSJU6QDBM","created_at":"2026-05-18T12:26:56.085431+00:00"},{"alias_kind":"pith_short_8","alias_value":"6AREZ7KW","created_at":"2026-05-18T12:26:56.085431+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG","json":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG.json","graph_json":"https://pith.science/api/pith-number/6AREZ7KWSJU6QDBM5KU53GTCDG/graph.json","events_json":"https://pith.science/api/pith-number/6AREZ7KWSJU6QDBM5KU53GTCDG/events.json","paper":"https://pith.science/paper/6AREZ7KW"},"agent_actions":{"view_html":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG","download_json":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG.json","view_paper":"https://pith.science/paper/6AREZ7KW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1207.0454&json=true","fetch_graph":"https://pith.science/api/pith-number/6AREZ7KWSJU6QDBM5KU53GTCDG/graph.json","fetch_events":"https://pith.science/api/pith-number/6AREZ7KWSJU6QDBM5KU53GTCDG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG/action/storage_attestation","attest_author":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG/action/author_attestation","sign_citation":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG/action/citation_signature","submit_replication":"https://pith.science/pith/6AREZ7KWSJU6QDBM5KU53GTCDG/action/replication_record"}},"created_at":"2026-05-18T03:51:59.297731+00:00","updated_at":"2026-05-18T03:51:59.297731+00:00"}