{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LIN6YVXCUTV4R5GWSVJ75FNQ4W","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":"42ca1c9b4b949c3a65930cf1bbd002e40e0259c6ac6897468fa42c1bf2a48bcf","cross_cats_sorted":["physics.med-ph"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-19T08:46:03Z","title_canon_sha256":"4dc1723c8d1b2922abaa1814f7c7812e8fc9b6328a4ea6c1acf1890881fa3b09"},"schema_version":"1.0","source":{"id":"2210.10379","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.10379","created_at":"2026-07-05T06:02:00Z"},{"alias_kind":"arxiv_version","alias_value":"2210.10379v3","created_at":"2026-07-05T06:02:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.10379","created_at":"2026-07-05T06:02:00Z"},{"alias_kind":"pith_short_12","alias_value":"LIN6YVXCUTV4","created_at":"2026-07-05T06:02:00Z"},{"alias_kind":"pith_short_16","alias_value":"LIN6YVXCUTV4R5GW","created_at":"2026-07-05T06:02:00Z"},{"alias_kind":"pith_short_8","alias_value":"LIN6YVXC","created_at":"2026-07-05T06:02:00Z"}],"graph_snapshots":[{"event_id":"sha256:121318de0ffafe0e215198772dbb8040025473eed574c6ef9a04c41e63b6f768","target":"graph","created_at":"2026-07-05T06:02:00Z","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/2210.10379/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Objective: Bloch simulation constitutes an essential part of magnetic resonance imaging (MRI) development. However, even with the graphics processing unit (GPU) acceleration, the heavy computational load remains a major challenge, especially in large-scale, high-accuracy simulation scenarios. This work aims to develop a deep learning-based simulator to accelerate Bloch simulation. Approach: The simulator model, called Simu-Net, is based on an end-to-end convolutional neural network and is trained with synthetic data generated by traditional Bloch simulation. It uses dynamic convolution to fuse","authors_text":"Congbo Cai, Haitao Huang, Jiechao Wang, Pujie Zhang, Qinqin Yang, Shuhui Cai","cross_cats":["physics.med-ph"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-19T08:46:03Z","title":"High-efficient Bloch simulation of magnetic resonance imaging sequences based on deep learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.10379","kind":"arxiv","version":3},"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:e491f667d9308d9325abc1d50c551994b49237a340dc58a9f65482f96d027fa4","target":"record","created_at":"2026-07-05T06:02:00Z","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":"42ca1c9b4b949c3a65930cf1bbd002e40e0259c6ac6897468fa42c1bf2a48bcf","cross_cats_sorted":["physics.med-ph"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-19T08:46:03Z","title_canon_sha256":"4dc1723c8d1b2922abaa1814f7c7812e8fc9b6328a4ea6c1acf1890881fa3b09"},"schema_version":"1.0","source":{"id":"2210.10379","kind":"arxiv","version":3}},"canonical_sha256":"5a1bec56e2a4ebc8f4d69553fe95b0e5a8470a53604ac85a3e315a5a6bc7acf2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a1bec56e2a4ebc8f4d69553fe95b0e5a8470a53604ac85a3e315a5a6bc7acf2","first_computed_at":"2026-07-05T06:02:00.616224Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:02:00.616224Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wTVApPe0jj2hYwtaAhxn1goe0cb1WcGwjeNGuH9KSP5o8rgSBkv0ZTjkeEBks075G2dLgDBKSLFvsfOkizmRAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:02:00.616625Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.10379","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e491f667d9308d9325abc1d50c551994b49237a340dc58a9f65482f96d027fa4","sha256:121318de0ffafe0e215198772dbb8040025473eed574c6ef9a04c41e63b6f768"],"state_sha256":"e975a09215f9ad7f446b32f048a47399f9bf5f148daf3eb8c623f424e5a79d13"}