{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:6USNZUTRYVTKDE4TJJCJWNKOJL","short_pith_number":"pith:6USNZUTR","canonical_record":{"source":{"id":"2509.10363","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T15:54:13Z","cross_cats_sorted":["cs.NA","math.NA"],"title_canon_sha256":"b3fafabf3afbadb0b4f8bc4cde780e8c109111ae20a19500309f4403c44c37f8","abstract_canon_sha256":"a3230e9eb00980bc337df81f10f88d7e2be6fe1efb54c88c5ca59c815207c227"},"schema_version":"1.0"},"canonical_sha256":"f524dcd271c566a193934a449b354e4aca2e58060bdd0059d7e79adfcdc8ea24","source":{"kind":"arxiv","id":"2509.10363","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.10363","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"arxiv_version","alias_value":"2509.10363v1","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.10363","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"pith_short_12","alias_value":"6USNZUTRYVTK","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"pith_short_16","alias_value":"6USNZUTRYVTKDE4T","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"pith_short_8","alias_value":"6USNZUTR","created_at":"2026-07-05T12:11:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:6USNZUTRYVTKDE4TJJCJWNKOJL","target":"record","payload":{"canonical_record":{"source":{"id":"2509.10363","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T15:54:13Z","cross_cats_sorted":["cs.NA","math.NA"],"title_canon_sha256":"b3fafabf3afbadb0b4f8bc4cde780e8c109111ae20a19500309f4403c44c37f8","abstract_canon_sha256":"a3230e9eb00980bc337df81f10f88d7e2be6fe1efb54c88c5ca59c815207c227"},"schema_version":"1.0"},"canonical_sha256":"f524dcd271c566a193934a449b354e4aca2e58060bdd0059d7e79adfcdc8ea24","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:11:08.416051Z","signature_b64":"l1n+Ti8sJjG1DZLLy971DsXxawqMD86/cQrhDnEAB6s0037QxoYgk3eepAdLDLDIR6ylvKMPBvD6CVxZsuWqCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f524dcd271c566a193934a449b354e4aca2e58060bdd0059d7e79adfcdc8ea24","last_reissued_at":"2026-07-05T12:11:08.415483Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:11:08.415483Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.10363","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":"2026-07-05T12:11:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XJ240FBTIUd1aht5XSzoE/pxgNRGSQst30eDrabOOg8fKh4+W9ZtBGIZfmKA7vZyu+73SvJb8uATxinHCpfaBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:49:50.096791Z"},"content_sha256":"7063ec01e8ddfc8d62fef1759857ee2eff1015012541a309f6325796d699714e","schema_version":"1.0","event_id":"sha256:7063ec01e8ddfc8d62fef1759857ee2eff1015012541a309f6325796d699714e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:6USNZUTRYVTKDE4TJJCJWNKOJL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Physics-informed sensor coverage through structure preserving machine learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NA","math.NA"],"primary_cat":"cs.LG","authors_text":"Benjamin David Shaffer, Brooks Kinch, Joseph Klobusicky, M. Ani Hsieh, Nathaniel Trask","submitted_at":"2025-09-12T15:54:13Z","abstract_excerpt":"We present a machine learning framework for adaptive source localization in which agents use a structure-preserving digital twin of a coupled hydrodynamic-transport system for real-time trajectory planning and data assimilation. The twin is constructed with conditional neural Whitney forms (CNWF), coupling the numerical guarantees of finite element exterior calculus (FEEC) with transformer-based operator learning. The resulting model preserves discrete conservation, and adapts in real time to streaming sensor data. It employs a conditional attention mechanism to identify: a reduced Whitney-for"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.10363","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/2509.10363/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":"2026-07-05T12:11:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D8U+MTP0DrhrqF/k3zLp1zfNyYVGz6c8M5O5sYYzj2lcUFNd75/wjS7yVpl1NJ3wAQlHshNwAA31cS1xkhsVBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:49:50.097210Z"},"content_sha256":"864fa00bccc751064de374eda70c11b08dd43ecaeb096ff6d452ef1b0de4b492","schema_version":"1.0","event_id":"sha256:864fa00bccc751064de374eda70c11b08dd43ecaeb096ff6d452ef1b0de4b492"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6USNZUTRYVTKDE4TJJCJWNKOJL/bundle.json","state_url":"https://pith.science/pith/6USNZUTRYVTKDE4TJJCJWNKOJL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6USNZUTRYVTKDE4TJJCJWNKOJL/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":"2026-08-07T16:49:50Z","links":{"resolver":"https://pith.science/pith/6USNZUTRYVTKDE4TJJCJWNKOJL","bundle":"https://pith.science/pith/6USNZUTRYVTKDE4TJJCJWNKOJL/bundle.json","state":"https://pith.science/pith/6USNZUTRYVTKDE4TJJCJWNKOJL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6USNZUTRYVTKDE4TJJCJWNKOJL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:6USNZUTRYVTKDE4TJJCJWNKOJL","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":"a3230e9eb00980bc337df81f10f88d7e2be6fe1efb54c88c5ca59c815207c227","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T15:54:13Z","title_canon_sha256":"b3fafabf3afbadb0b4f8bc4cde780e8c109111ae20a19500309f4403c44c37f8"},"schema_version":"1.0","source":{"id":"2509.10363","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.10363","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"arxiv_version","alias_value":"2509.10363v1","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.10363","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"pith_short_12","alias_value":"6USNZUTRYVTK","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"pith_short_16","alias_value":"6USNZUTRYVTKDE4T","created_at":"2026-07-05T12:11:08Z"},{"alias_kind":"pith_short_8","alias_value":"6USNZUTR","created_at":"2026-07-05T12:11:08Z"}],"graph_snapshots":[{"event_id":"sha256:864fa00bccc751064de374eda70c11b08dd43ecaeb096ff6d452ef1b0de4b492","target":"graph","created_at":"2026-07-05T12:11:08Z","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/2509.10363/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a machine learning framework for adaptive source localization in which agents use a structure-preserving digital twin of a coupled hydrodynamic-transport system for real-time trajectory planning and data assimilation. The twin is constructed with conditional neural Whitney forms (CNWF), coupling the numerical guarantees of finite element exterior calculus (FEEC) with transformer-based operator learning. The resulting model preserves discrete conservation, and adapts in real time to streaming sensor data. It employs a conditional attention mechanism to identify: a reduced Whitney-for","authors_text":"Benjamin David Shaffer, Brooks Kinch, Joseph Klobusicky, M. Ani Hsieh, Nathaniel Trask","cross_cats":["cs.NA","math.NA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T15:54:13Z","title":"Physics-informed sensor coverage through structure preserving machine learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.10363","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":"sha256:7063ec01e8ddfc8d62fef1759857ee2eff1015012541a309f6325796d699714e","target":"record","created_at":"2026-07-05T12:11:08Z","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":"a3230e9eb00980bc337df81f10f88d7e2be6fe1efb54c88c5ca59c815207c227","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T15:54:13Z","title_canon_sha256":"b3fafabf3afbadb0b4f8bc4cde780e8c109111ae20a19500309f4403c44c37f8"},"schema_version":"1.0","source":{"id":"2509.10363","kind":"arxiv","version":1}},"canonical_sha256":"f524dcd271c566a193934a449b354e4aca2e58060bdd0059d7e79adfcdc8ea24","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f524dcd271c566a193934a449b354e4aca2e58060bdd0059d7e79adfcdc8ea24","first_computed_at":"2026-07-05T12:11:08.415483Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:11:08.415483Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l1n+Ti8sJjG1DZLLy971DsXxawqMD86/cQrhDnEAB6s0037QxoYgk3eepAdLDLDIR6ylvKMPBvD6CVxZsuWqCw==","signature_status":"signed_v1","signed_at":"2026-07-05T12:11:08.416051Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.10363","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7063ec01e8ddfc8d62fef1759857ee2eff1015012541a309f6325796d699714e","sha256:864fa00bccc751064de374eda70c11b08dd43ecaeb096ff6d452ef1b0de4b492"],"state_sha256":"d71f7b5baa2b387cccf4e62336544c7928b34cafb653095051b3e2ba0f78c481"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RarGLbWoxhGAadR39Qlif3WtFrxUDjrFi7Mc02JH2uwxj70UXdEg3y0kgvn4d0PhCIozhbVP7KS+GNFqoVb9CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T16:49:50.099928Z","bundle_sha256":"6e87fcb15d71e1a25e6227e2efa976fca7d96a1f510a9615bcc4c5b523f22d97"}}