{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VQUA2LHHCX3YNVLZZGYMZCE5QS","short_pith_number":"pith:VQUA2LHH","canonical_record":{"source":{"id":"2502.13370","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-19T02:09:43Z","cross_cats_sorted":["cs.NA","math.NA","quant-ph"],"title_canon_sha256":"96b92a221f8b4dbd9688bd22656d422c874eb3d28c1c1bf394bd639999ad71b3","abstract_canon_sha256":"12e3f901a6a489bf48bde09283f3262958e8c5a93d78dea58788afa0d2e635ac"},"schema_version":"1.0"},"canonical_sha256":"ac280d2ce715f786d579c9b0cc889d84b8b5c18bc324d91ae01b9c51844fce89","source":{"kind":"arxiv","id":"2502.13370","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.13370","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"arxiv_version","alias_value":"2502.13370v1","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.13370","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"pith_short_12","alias_value":"VQUA2LHHCX3Y","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"pith_short_16","alias_value":"VQUA2LHHCX3YNVLZ","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"pith_short_8","alias_value":"VQUA2LHH","created_at":"2026-07-05T10:16:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VQUA2LHHCX3YNVLZZGYMZCE5QS","target":"record","payload":{"canonical_record":{"source":{"id":"2502.13370","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-19T02:09:43Z","cross_cats_sorted":["cs.NA","math.NA","quant-ph"],"title_canon_sha256":"96b92a221f8b4dbd9688bd22656d422c874eb3d28c1c1bf394bd639999ad71b3","abstract_canon_sha256":"12e3f901a6a489bf48bde09283f3262958e8c5a93d78dea58788afa0d2e635ac"},"schema_version":"1.0"},"canonical_sha256":"ac280d2ce715f786d579c9b0cc889d84b8b5c18bc324d91ae01b9c51844fce89","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:16:46.071837Z","signature_b64":"oRoHEtyi/wwfdMAlheM6erD11pMRcJ2Izfm9g2PGFb3kEXRANV3RvKjjEBVVsbuU+Fk9SpmCu17eT4OXi6yFDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac280d2ce715f786d579c9b0cc889d84b8b5c18bc324d91ae01b9c51844fce89","last_reissued_at":"2026-07-05T10:16:46.071353Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:16:46.071353Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.13370","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":"2026-07-05T10:16:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eeGdlAuxUjSUZSRgbJZCijLlmSDYZUwn5SeHFQDZhjKs5WHB1uUco1IEcgORaqkuNeMotdy7Kse9RwULkPAaCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T08:50:48.998965Z"},"content_sha256":"d5aac85b06e24a9097ccb34323a72d1c46d771a7ae3404b7fc229cbf309cd7f6","schema_version":"1.0","event_id":"sha256:d5aac85b06e24a9097ccb34323a72d1c46d771a7ae3404b7fc229cbf309cd7f6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VQUA2LHHCX3YNVLZZGYMZCE5QS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Quantum Recurrent Neural Networks with Encoder-Decoder for Time-Dependent Partial Differential Equations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA","math.NA","quant-ph"],"primary_cat":"cs.LG","authors_text":"Abdul Khaliq, Khaled M. Furati, Yuan Chen","submitted_at":"2025-02-19T02:09:43Z","abstract_excerpt":"Nonlinear time-dependent partial differential equations are essential in modeling complex phenomena across diverse fields, yet they pose significant challenges due to their computational complexity, especially in higher dimensions. This study explores Quantum Recurrent Neural Networks within an encoder-decoder framework, integrating Variational Quantum Circuits into Gated Recurrent Units and Long Short-Term Memory networks. Using this architecture, the model efficiently compresses high-dimensional spatiotemporal data into a compact latent space, facilitating more efficient temporal evolution. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.13370","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/2502.13370/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":"2026-07-05T10:16:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Yr25APa8LanndOJQCoeWVKn8yWyOLKK9Fc/yySJZSMo9kZPeVD4Bnm6kZ2gdELUL32zvShmV+Oar6AOVj3XTBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T08:50:48.999492Z"},"content_sha256":"6f311a3f34d15a705f458d610e61bc14a19bfea451808e3876589acc446ddfb0","schema_version":"1.0","event_id":"sha256:6f311a3f34d15a705f458d610e61bc14a19bfea451808e3876589acc446ddfb0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VQUA2LHHCX3YNVLZZGYMZCE5QS/bundle.json","state_url":"https://pith.science/pith/VQUA2LHHCX3YNVLZZGYMZCE5QS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VQUA2LHHCX3YNVLZZGYMZCE5QS/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":"2026-08-20T08:50:49Z","links":{"resolver":"https://pith.science/pith/VQUA2LHHCX3YNVLZZGYMZCE5QS","bundle":"https://pith.science/pith/VQUA2LHHCX3YNVLZZGYMZCE5QS/bundle.json","state":"https://pith.science/pith/VQUA2LHHCX3YNVLZZGYMZCE5QS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VQUA2LHHCX3YNVLZZGYMZCE5QS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VQUA2LHHCX3YNVLZZGYMZCE5QS","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":"12e3f901a6a489bf48bde09283f3262958e8c5a93d78dea58788afa0d2e635ac","cross_cats_sorted":["cs.NA","math.NA","quant-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-19T02:09:43Z","title_canon_sha256":"96b92a221f8b4dbd9688bd22656d422c874eb3d28c1c1bf394bd639999ad71b3"},"schema_version":"1.0","source":{"id":"2502.13370","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.13370","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"arxiv_version","alias_value":"2502.13370v1","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.13370","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"pith_short_12","alias_value":"VQUA2LHHCX3Y","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"pith_short_16","alias_value":"VQUA2LHHCX3YNVLZ","created_at":"2026-07-05T10:16:46Z"},{"alias_kind":"pith_short_8","alias_value":"VQUA2LHH","created_at":"2026-07-05T10:16:46Z"}],"graph_snapshots":[{"event_id":"sha256:6f311a3f34d15a705f458d610e61bc14a19bfea451808e3876589acc446ddfb0","target":"graph","created_at":"2026-07-05T10:16:46Z","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/2502.13370/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Nonlinear time-dependent partial differential equations are essential in modeling complex phenomena across diverse fields, yet they pose significant challenges due to their computational complexity, especially in higher dimensions. This study explores Quantum Recurrent Neural Networks within an encoder-decoder framework, integrating Variational Quantum Circuits into Gated Recurrent Units and Long Short-Term Memory networks. Using this architecture, the model efficiently compresses high-dimensional spatiotemporal data into a compact latent space, facilitating more efficient temporal evolution. ","authors_text":"Abdul Khaliq, Khaled M. Furati, Yuan Chen","cross_cats":["cs.NA","math.NA","quant-ph"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-19T02:09:43Z","title":"Quantum Recurrent Neural Networks with Encoder-Decoder for Time-Dependent Partial Differential Equations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.13370","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:d5aac85b06e24a9097ccb34323a72d1c46d771a7ae3404b7fc229cbf309cd7f6","target":"record","created_at":"2026-07-05T10:16:46Z","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":"12e3f901a6a489bf48bde09283f3262958e8c5a93d78dea58788afa0d2e635ac","cross_cats_sorted":["cs.NA","math.NA","quant-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-19T02:09:43Z","title_canon_sha256":"96b92a221f8b4dbd9688bd22656d422c874eb3d28c1c1bf394bd639999ad71b3"},"schema_version":"1.0","source":{"id":"2502.13370","kind":"arxiv","version":1}},"canonical_sha256":"ac280d2ce715f786d579c9b0cc889d84b8b5c18bc324d91ae01b9c51844fce89","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ac280d2ce715f786d579c9b0cc889d84b8b5c18bc324d91ae01b9c51844fce89","first_computed_at":"2026-07-05T10:16:46.071353Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:16:46.071353Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oRoHEtyi/wwfdMAlheM6erD11pMRcJ2Izfm9g2PGFb3kEXRANV3RvKjjEBVVsbuU+Fk9SpmCu17eT4OXi6yFDg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:16:46.071837Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.13370","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d5aac85b06e24a9097ccb34323a72d1c46d771a7ae3404b7fc229cbf309cd7f6","sha256:6f311a3f34d15a705f458d610e61bc14a19bfea451808e3876589acc446ddfb0"],"state_sha256":"702d6b6c18b550d9b10cd2af873bae2fcaf47ed942ef9d8301e906053dc92da1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xbGSR4AeagTuml4tRsiKjiXlAoX8VRwJgb4u8sxothGWgbcssm12JcvjwU+VXcyWb0pD5RvkWiJtmSaBK6heCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T08:50:49.005386Z","bundle_sha256":"f6eeeb87ba1b86f1582179921ef6ebf4d38614de44746ac80bdb9fc72b56d70e"}}