{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ZUIQELOHDFLGXLFFFGF6CFMEZR","short_pith_number":"pith:ZUIQELOH","canonical_record":{"source":{"id":"2410.13141","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T01:57:04Z","cross_cats_sorted":["physics.comp-ph"],"title_canon_sha256":"f901a846e0e5708032022b046e3854743ebf6137164b37ae9df40ca73d15c843","abstract_canon_sha256":"4d110d03d89c13c05a39f42a1018bb80a26576e9b1c97b13857ad7037816b58c"},"schema_version":"1.0"},"canonical_sha256":"cd11022dc719566baca5298be11584cc59e579a8271c9949398140eab9fb5bb5","source":{"kind":"arxiv","id":"2410.13141","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.13141","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"arxiv_version","alias_value":"2410.13141v1","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.13141","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"pith_short_12","alias_value":"ZUIQELOHDFLG","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"pith_short_16","alias_value":"ZUIQELOHDFLGXLFF","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"pith_short_8","alias_value":"ZUIQELOH","created_at":"2026-07-05T09:21:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ZUIQELOHDFLGXLFFFGF6CFMEZR","target":"record","payload":{"canonical_record":{"source":{"id":"2410.13141","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T01:57:04Z","cross_cats_sorted":["physics.comp-ph"],"title_canon_sha256":"f901a846e0e5708032022b046e3854743ebf6137164b37ae9df40ca73d15c843","abstract_canon_sha256":"4d110d03d89c13c05a39f42a1018bb80a26576e9b1c97b13857ad7037816b58c"},"schema_version":"1.0"},"canonical_sha256":"cd11022dc719566baca5298be11584cc59e579a8271c9949398140eab9fb5bb5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:21:56.291251Z","signature_b64":"8qRx195f2ghypTuL4qlfdEDz3IDdP16KZEZV2Vaf63faBHa0bLlwjpgmW6FSkk1ujgx28LMyU2dJoq7zixlvDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd11022dc719566baca5298be11584cc59e579a8271c9949398140eab9fb5bb5","last_reissued_at":"2026-07-05T09:21:56.290774Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:21:56.290774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.13141","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":"2026-07-05T09:21:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iziLy2Rf5SMRNfyqu/NtwtVx1bGg3EdSICSKkKHkZxI00lVzbLnAqgfyoDaMkx6aUbZfFy/ETPKZeZuSKcYABA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T17:13:23.667767Z"},"content_sha256":"1ce37415f6fe6d133bde346da85a34b7311bb125ad49ec57d4636003554de161","schema_version":"1.0","event_id":"sha256:1ce37415f6fe6d133bde346da85a34b7311bb125ad49ec57d4636003554de161"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ZUIQELOHDFLGXLFFFGF6CFMEZR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["physics.comp-ph"],"primary_cat":"cs.LG","authors_text":"Handi Zhang, Langchen Liu, Lu Lu","submitted_at":"2024-10-17T01:57:04Z","abstract_excerpt":"By leveraging neural networks, the emerging field of scientific machine learning (SciML) offers novel approaches to address complex problems governed by partial differential equations (PDEs). In practical applications, challenges arise due to the distributed essence of data, concerns about data privacy, or the impracticality of transferring large volumes of data. Federated learning (FL), a decentralized framework that enables the collaborative training of a global model while preserving data privacy, offers a solution to the challenges posed by isolated data pools and sensitive data issues. He"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.13141","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/2410.13141/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":"2026-07-05T09:21:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JLCuwOb54DJ812gWBu/6R7CNf8X2ruLBS5aAhLHCrVC3xFNwHzBIsWjpN3ULgAjPvRJZ2kPz2UX36ssQZAuiDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T17:13:23.668715Z"},"content_sha256":"146131b806b15aa126f3ad7d2b9e77e02843d279b0f20ce0c18b7d63d9e24f76","schema_version":"1.0","event_id":"sha256:146131b806b15aa126f3ad7d2b9e77e02843d279b0f20ce0c18b7d63d9e24f76"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZUIQELOHDFLGXLFFFGF6CFMEZR/bundle.json","state_url":"https://pith.science/pith/ZUIQELOHDFLGXLFFFGF6CFMEZR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZUIQELOHDFLGXLFFFGF6CFMEZR/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":"2026-08-08T17:13:23Z","links":{"resolver":"https://pith.science/pith/ZUIQELOHDFLGXLFFFGF6CFMEZR","bundle":"https://pith.science/pith/ZUIQELOHDFLGXLFFFGF6CFMEZR/bundle.json","state":"https://pith.science/pith/ZUIQELOHDFLGXLFFFGF6CFMEZR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZUIQELOHDFLGXLFFFGF6CFMEZR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZUIQELOHDFLGXLFFFGF6CFMEZR","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":"4d110d03d89c13c05a39f42a1018bb80a26576e9b1c97b13857ad7037816b58c","cross_cats_sorted":["physics.comp-ph"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T01:57:04Z","title_canon_sha256":"f901a846e0e5708032022b046e3854743ebf6137164b37ae9df40ca73d15c843"},"schema_version":"1.0","source":{"id":"2410.13141","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.13141","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"arxiv_version","alias_value":"2410.13141v1","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.13141","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"pith_short_12","alias_value":"ZUIQELOHDFLG","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"pith_short_16","alias_value":"ZUIQELOHDFLGXLFF","created_at":"2026-07-05T09:21:56Z"},{"alias_kind":"pith_short_8","alias_value":"ZUIQELOH","created_at":"2026-07-05T09:21:56Z"}],"graph_snapshots":[{"event_id":"sha256:146131b806b15aa126f3ad7d2b9e77e02843d279b0f20ce0c18b7d63d9e24f76","target":"graph","created_at":"2026-07-05T09:21:56Z","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/2410.13141/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"By leveraging neural networks, the emerging field of scientific machine learning (SciML) offers novel approaches to address complex problems governed by partial differential equations (PDEs). In practical applications, challenges arise due to the distributed essence of data, concerns about data privacy, or the impracticality of transferring large volumes of data. Federated learning (FL), a decentralized framework that enables the collaborative training of a global model while preserving data privacy, offers a solution to the challenges posed by isolated data pools and sensitive data issues. He","authors_text":"Handi Zhang, Langchen Liu, Lu Lu","cross_cats":["physics.comp-ph"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T01:57:04Z","title":"Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.13141","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":"sha256:1ce37415f6fe6d133bde346da85a34b7311bb125ad49ec57d4636003554de161","target":"record","created_at":"2026-07-05T09:21:56Z","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":"4d110d03d89c13c05a39f42a1018bb80a26576e9b1c97b13857ad7037816b58c","cross_cats_sorted":["physics.comp-ph"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T01:57:04Z","title_canon_sha256":"f901a846e0e5708032022b046e3854743ebf6137164b37ae9df40ca73d15c843"},"schema_version":"1.0","source":{"id":"2410.13141","kind":"arxiv","version":1}},"canonical_sha256":"cd11022dc719566baca5298be11584cc59e579a8271c9949398140eab9fb5bb5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cd11022dc719566baca5298be11584cc59e579a8271c9949398140eab9fb5bb5","first_computed_at":"2026-07-05T09:21:56.290774Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:21:56.290774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8qRx195f2ghypTuL4qlfdEDz3IDdP16KZEZV2Vaf63faBHa0bLlwjpgmW6FSkk1ujgx28LMyU2dJoq7zixlvDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:21:56.291251Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.13141","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ce37415f6fe6d133bde346da85a34b7311bb125ad49ec57d4636003554de161","sha256:146131b806b15aa126f3ad7d2b9e77e02843d279b0f20ce0c18b7d63d9e24f76"],"state_sha256":"1f305e0ad9291fde4c2fd1622f0c7a2ca27c21f5d56b824e82fa815d6a8c9d64"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZiXb3ZCVJSWymDDfDoTD2F7wZxELtXrzu6XyJNq8EiNpNNZtfoSieUD41uu5o6DbMraZNyzFfBWYMCfMmDK4Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T17:13:23.692247Z","bundle_sha256":"564089c90cd19f5e8b58ff88ac32c20fc8d3ecded15708bb04d7c24ebb568f3a"}}