{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2AVPKVMUMTS3L4664GVGJHTQXV","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":"84ac707fe66702bd29717ce7ff7c79f72583d2d957173ed4b67d39bffb80f06d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2025-03-19T17:30:57Z","title_canon_sha256":"ca248644d51d753172cbc5b61a5c18593c22b597b68488183a37c48c7f38437e"},"schema_version":"1.0","source":{"id":"2503.17400","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.17400","created_at":"2026-06-09T02:07:02Z"},{"alias_kind":"arxiv_version","alias_value":"2503.17400v2","created_at":"2026-06-09T02:07:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.17400","created_at":"2026-06-09T02:07:02Z"},{"alias_kind":"pith_short_12","alias_value":"2AVPKVMUMTS3","created_at":"2026-06-09T02:07:02Z"},{"alias_kind":"pith_short_16","alias_value":"2AVPKVMUMTS3L466","created_at":"2026-06-09T02:07:02Z"},{"alias_kind":"pith_short_8","alias_value":"2AVPKVMU","created_at":"2026-06-09T02:07:02Z"}],"graph_snapshots":[{"event_id":"sha256:e6e5240de3d429986fd50195bee78c1d73c00917a358d0851729b1cbdd2ac42e","target":"graph","created_at":"2026-06-09T02:07:02Z","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/2503.17400/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Surrogate modeling has emerged as a powerful tool to accelerate Computational Fluid Dynamics (CFD) simulations. Existing 3D geometric learning models based on point clouds, voxels, meshes, or graphs depend on explicit geometric representations that are memory-intensive and resolution-limited. For large-scale simulations with millions of nodes and cells, existing models require aggressive downsampling due to their dependence on mesh resolution, resulting in degraded accuracy. We present TripNet, a triplane-based neural framework that implicitly encodes 3D geometry into a compact, continuous fea","authors_text":"Angela Dai, Faez Ahmed, Mohamed Elrefaie, Qian Chen","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2025-03-19T17:30:57Z","title":"TripNet: Learning Large-scale High-fidelity 3D Car Aerodynamics with Triplane Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.17400","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":"sha256:1b3b353a3e90697c899e8984e279e31bd5f28a736e1ea954f5155416c4455af6","target":"record","created_at":"2026-06-09T02:07:02Z","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":"84ac707fe66702bd29717ce7ff7c79f72583d2d957173ed4b67d39bffb80f06d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2025-03-19T17:30:57Z","title_canon_sha256":"ca248644d51d753172cbc5b61a5c18593c22b597b68488183a37c48c7f38437e"},"schema_version":"1.0","source":{"id":"2503.17400","kind":"arxiv","version":2}},"canonical_sha256":"d02af5559464e5b5f3dee1aa649e70bd4a1fa2368dfca8ba6109ad168a831e5a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d02af5559464e5b5f3dee1aa649e70bd4a1fa2368dfca8ba6109ad168a831e5a","first_computed_at":"2026-06-09T02:07:02.750420Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-09T02:07:02.750420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2FtqDGwQzW4BPHnr0XP6J1sI8XqbS9nI23LGYRNa7+zlUyFP3zVn/ngimmieDtS42ekf8ysQZUmUmshwizTpDQ==","signature_status":"signed_v1","signed_at":"2026-06-09T02:07:02.751533Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.17400","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b3b353a3e90697c899e8984e279e31bd5f28a736e1ea954f5155416c4455af6","sha256:e6e5240de3d429986fd50195bee78c1d73c00917a358d0851729b1cbdd2ac42e"],"state_sha256":"0e1e17d6edcbffabdb548c9f5f6f091e6ef5acb0373110fe9b33b011904e05ae"}