{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:QNVBRVLBHONLRNIINECYL7Q77K","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":"44c2a72b2e3154795ae42e7279ac148600bffc4b8b58564ce13d9bddf318b478","cross_cats_sorted":["cs.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-06-05T10:24:20Z","title_canon_sha256":"605d13f462cd798706011154e373d0aff9045914750a2a5f37d1dfd92d049e9e"},"schema_version":"1.0","source":{"id":"2606.07122","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.07122","created_at":"2026-06-08T01:04:47Z"},{"alias_kind":"arxiv_version","alias_value":"2606.07122v1","created_at":"2026-06-08T01:04:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.07122","created_at":"2026-06-08T01:04:47Z"},{"alias_kind":"pith_short_12","alias_value":"QNVBRVLBHONL","created_at":"2026-06-08T01:04:47Z"},{"alias_kind":"pith_short_16","alias_value":"QNVBRVLBHONLRNII","created_at":"2026-06-08T01:04:47Z"},{"alias_kind":"pith_short_8","alias_value":"QNVBRVLB","created_at":"2026-06-08T01:04:47Z"}],"graph_snapshots":[{"event_id":"sha256:ec26e3e469588c020f671148a1778fb7109a76bf3b0f891e83f5ec42a1a41061","target":"graph","created_at":"2026-06-08T01:04:47Z","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/2606.07122/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We develop a unified DeepONet framework for logarithmically stable infinite-dimensional inverse problems, with inverse acoustic scattering as a model application. The framework is formulated at the operator level by separating the learned inverse map into measurement encoding, finite-dimensional neural approximation, and functional reconstruction components. For inverse maps satisfying a logarithmic stability estimate, we establish quantitative a priori error bounds giving separate estimates for the encoder error, the neural approximation error, and the reconstruction error, thereby characteri","authors_text":"Tiexiang Li, Wen-Jie Wu, Wen-Wei Lin","cross_cats":["cs.NA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-06-05T10:24:20Z","title":"A Unified DeepONet Framework for Logarithmically Stable Infinite-Dimensional Inverse Problems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.07122","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":"sha256:9589bfb1e67c8b05a3ea541792f62aff437bac372bba627c267dc071723230c9","target":"record","created_at":"2026-06-08T01:04:47Z","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":"44c2a72b2e3154795ae42e7279ac148600bffc4b8b58564ce13d9bddf318b478","cross_cats_sorted":["cs.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-06-05T10:24:20Z","title_canon_sha256":"605d13f462cd798706011154e373d0aff9045914750a2a5f37d1dfd92d049e9e"},"schema_version":"1.0","source":{"id":"2606.07122","kind":"arxiv","version":1}},"canonical_sha256":"836a18d5613b9ab8b508690585fe1ffaa9857c38e18debad9329a4f4e31286ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"836a18d5613b9ab8b508690585fe1ffaa9857c38e18debad9329a4f4e31286ba","first_computed_at":"2026-06-08T01:04:47.568291Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-08T01:04:47.568291Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JbF3IG4H/SEznnD78JWDiyXq7vj/25tYfrSvA8VohNMp4d0Xw/6REDD3BzA3K8BDooGZu32kgC4SG9U6ty2UDw==","signature_status":"signed_v1","signed_at":"2026-06-08T01:04:47.569139Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.07122","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9589bfb1e67c8b05a3ea541792f62aff437bac372bba627c267dc071723230c9","sha256:ec26e3e469588c020f671148a1778fb7109a76bf3b0f891e83f5ec42a1a41061"],"state_sha256":"924b0127e2a6218c5a565c02fe1dd86c2b7a51390616b8daf700b540a242a9b9"}