{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:6Q4CIX2LUSHQPEIVGPANLTDO25","short_pith_number":"pith:6Q4CIX2L","canonical_record":{"source":{"id":"2210.04259","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2022-10-09T13:21:28Z","cross_cats_sorted":[],"title_canon_sha256":"3ae71951fa2661025e9929b88852712080fdb7ef1950c8d9c15d4bb33ca67bd9","abstract_canon_sha256":"fa56d69b2f2217a62f24f4dd8cdc59d76058c45539b014b8bccbcd31d9a4af47"},"schema_version":"1.0"},"canonical_sha256":"f438245f4ba48f07911533c0d5cc6ed762c57b4b7dfc92b32d29c630b00a1347","source":{"kind":"arxiv","id":"2210.04259","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.04259","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"arxiv_version","alias_value":"2210.04259v2","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.04259","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"pith_short_12","alias_value":"6Q4CIX2LUSHQ","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"pith_short_16","alias_value":"6Q4CIX2LUSHQPEIV","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"pith_short_8","alias_value":"6Q4CIX2L","created_at":"2026-07-05T05:19:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:6Q4CIX2LUSHQPEIVGPANLTDO25","target":"record","payload":{"canonical_record":{"source":{"id":"2210.04259","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2022-10-09T13:21:28Z","cross_cats_sorted":[],"title_canon_sha256":"3ae71951fa2661025e9929b88852712080fdb7ef1950c8d9c15d4bb33ca67bd9","abstract_canon_sha256":"fa56d69b2f2217a62f24f4dd8cdc59d76058c45539b014b8bccbcd31d9a4af47"},"schema_version":"1.0"},"canonical_sha256":"f438245f4ba48f07911533c0d5cc6ed762c57b4b7dfc92b32d29c630b00a1347","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:19:19.369943Z","signature_b64":"W6AExGN8ZCDcHyDAo44tmWDrk/gQFixRwBGSSx6Ax6MzT+UCslfZcgBn0bLNIOixiqAX1nha6IwkHy7dTMNIBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f438245f4ba48f07911533c0d5cc6ed762c57b4b7dfc92b32d29c630b00a1347","last_reissued_at":"2026-07-05T05:19:19.369553Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:19:19.369553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.04259","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:19:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q0CwGp6G8XJvVaqDP1c60VdinLCTixm8PH0wfrBCYzNhJybMihaXKzogilf4Y6E6OjEdM+fltg0X5gxY2OAVDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T18:44:49.589811Z"},"content_sha256":"7a0c998eb40d81fb922340389b6cd0430afc1d78ab75583296ca8026d7501dbe","schema_version":"1.0","event_id":"sha256:7a0c998eb40d81fb922340389b6cd0430afc1d78ab75583296ca8026d7501dbe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:6Q4CIX2LUSHQPEIVGPANLTDO25","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Linear attention coupled Fourier neural operator for simulation of three-dimensional turbulence","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.flu-dyn","authors_text":"Jianchun Wang, Wenhui Peng, Zelong Yuan, Zhijie Li","submitted_at":"2022-10-09T13:21:28Z","abstract_excerpt":"Modeling three-dimensional (3D) turbulence by neural networks is difficult because 3D turbulence is highly-nonlinear with high degrees of freedom and the corresponding simulation is memory-intensive. Recently, the attention mechanism has been shown as a promising approach to boost the performance of neural networks on turbulence simulation. However, the standard self-attention mechanism uses $O(n^2)$ time and space with respect to input dimension $n$, and such quadratic complexity has become the main bottleneck for attention to be applied on 3D turbulence simulation. In this work, we resolve t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.04259","kind":"arxiv","version":2},"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/2210.04259/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":"2026-07-05T05:19:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zQd2kgnm3cLc+RvFgJZMhb9LP/A8xIlaQI5Ijw5ekXFK8Gqw+YBG/ckPj/vubFnS6y5Df1kcvga2vMzVE8BFBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T18:44:49.590857Z"},"content_sha256":"5bdf018cebaf53d59352f270150aec0114912fc0dc666aae27ed75b290feb4f3","schema_version":"1.0","event_id":"sha256:5bdf018cebaf53d59352f270150aec0114912fc0dc666aae27ed75b290feb4f3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6Q4CIX2LUSHQPEIVGPANLTDO25/bundle.json","state_url":"https://pith.science/pith/6Q4CIX2LUSHQPEIVGPANLTDO25/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6Q4CIX2LUSHQPEIVGPANLTDO25/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":"2026-08-10T18:44:49Z","links":{"resolver":"https://pith.science/pith/6Q4CIX2LUSHQPEIVGPANLTDO25","bundle":"https://pith.science/pith/6Q4CIX2LUSHQPEIVGPANLTDO25/bundle.json","state":"https://pith.science/pith/6Q4CIX2LUSHQPEIVGPANLTDO25/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6Q4CIX2LUSHQPEIVGPANLTDO25/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:6Q4CIX2LUSHQPEIVGPANLTDO25","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":"fa56d69b2f2217a62f24f4dd8cdc59d76058c45539b014b8bccbcd31d9a4af47","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2022-10-09T13:21:28Z","title_canon_sha256":"3ae71951fa2661025e9929b88852712080fdb7ef1950c8d9c15d4bb33ca67bd9"},"schema_version":"1.0","source":{"id":"2210.04259","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.04259","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"arxiv_version","alias_value":"2210.04259v2","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.04259","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"pith_short_12","alias_value":"6Q4CIX2LUSHQ","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"pith_short_16","alias_value":"6Q4CIX2LUSHQPEIV","created_at":"2026-07-05T05:19:19Z"},{"alias_kind":"pith_short_8","alias_value":"6Q4CIX2L","created_at":"2026-07-05T05:19:19Z"}],"graph_snapshots":[{"event_id":"sha256:5bdf018cebaf53d59352f270150aec0114912fc0dc666aae27ed75b290feb4f3","target":"graph","created_at":"2026-07-05T05:19:19Z","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/2210.04259/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Modeling three-dimensional (3D) turbulence by neural networks is difficult because 3D turbulence is highly-nonlinear with high degrees of freedom and the corresponding simulation is memory-intensive. Recently, the attention mechanism has been shown as a promising approach to boost the performance of neural networks on turbulence simulation. However, the standard self-attention mechanism uses $O(n^2)$ time and space with respect to input dimension $n$, and such quadratic complexity has become the main bottleneck for attention to be applied on 3D turbulence simulation. In this work, we resolve t","authors_text":"Jianchun Wang, Wenhui Peng, Zelong Yuan, Zhijie Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2022-10-09T13:21:28Z","title":"Linear attention coupled Fourier neural operator for simulation of three-dimensional turbulence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.04259","kind":"arxiv","version":2},"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":"sha256:7a0c998eb40d81fb922340389b6cd0430afc1d78ab75583296ca8026d7501dbe","target":"record","created_at":"2026-07-05T05:19:19Z","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":"fa56d69b2f2217a62f24f4dd8cdc59d76058c45539b014b8bccbcd31d9a4af47","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2022-10-09T13:21:28Z","title_canon_sha256":"3ae71951fa2661025e9929b88852712080fdb7ef1950c8d9c15d4bb33ca67bd9"},"schema_version":"1.0","source":{"id":"2210.04259","kind":"arxiv","version":2}},"canonical_sha256":"f438245f4ba48f07911533c0d5cc6ed762c57b4b7dfc92b32d29c630b00a1347","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f438245f4ba48f07911533c0d5cc6ed762c57b4b7dfc92b32d29c630b00a1347","first_computed_at":"2026-07-05T05:19:19.369553Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:19:19.369553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W6AExGN8ZCDcHyDAo44tmWDrk/gQFixRwBGSSx6Ax6MzT+UCslfZcgBn0bLNIOixiqAX1nha6IwkHy7dTMNIBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:19:19.369943Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.04259","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7a0c998eb40d81fb922340389b6cd0430afc1d78ab75583296ca8026d7501dbe","sha256:5bdf018cebaf53d59352f270150aec0114912fc0dc666aae27ed75b290feb4f3"],"state_sha256":"4358f4ef4451ce91f71b1ddd9df90dc9dda93fbabf016cfe7939e5befa9772c7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dhzu+A5Bj9SDvVQ/9hG3XZ1WXk5n+SkCRL6GTdVOTytIZiXMo4dzmMNZDWQh30WfeQzE1Nd+E0Ja5uiXSS1uDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T18:44:49.597073Z","bundle_sha256":"0161582ad5367f534b145913953fa930365fe073bbac1f8c889d4a9ff127cf04"}}