{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:GXL467GWBKZER2TURI7EMGXG75","short_pith_number":"pith:GXL467GW","canonical_record":{"source":{"id":"2605.21499","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-05T16:03:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"075f0b74226981ee73aa3cd1f3c81b821140b9e0bf8b7ca4cc2e4fe437fdaf69","abstract_canon_sha256":"efe176f3b751ab95199008d56a091c83d5861279c43210ef210bd3782c4bb6d1"},"schema_version":"1.0"},"canonical_sha256":"35d7cf7cd60ab248ea748a3e461ae6ff4b1f29fb6937a08c054f172a6bd3cffa","source":{"kind":"arxiv","id":"2605.21499","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.21499","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"arxiv_version","alias_value":"2605.21499v1","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.21499","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"pith_short_12","alias_value":"GXL467GWBKZE","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"pith_short_16","alias_value":"GXL467GWBKZER2TU","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"pith_short_8","alias_value":"GXL467GW","created_at":"2026-05-22T00:02:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:GXL467GWBKZER2TURI7EMGXG75","target":"record","payload":{"canonical_record":{"source":{"id":"2605.21499","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-05T16:03:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"075f0b74226981ee73aa3cd1f3c81b821140b9e0bf8b7ca4cc2e4fe437fdaf69","abstract_canon_sha256":"efe176f3b751ab95199008d56a091c83d5861279c43210ef210bd3782c4bb6d1"},"schema_version":"1.0"},"canonical_sha256":"35d7cf7cd60ab248ea748a3e461ae6ff4b1f29fb6937a08c054f172a6bd3cffa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T00:02:27.050961Z","signature_b64":"3HKzogMmRA/MOauOeOnDsbLfIHkHPjYEXpeIOQl9Tg6sYVr+FBpPP/Uiv6YMgH0EmvXWrf/NgLQ/MtPXncxDDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"35d7cf7cd60ab248ea748a3e461ae6ff4b1f29fb6937a08c054f172a6bd3cffa","last_reissued_at":"2026-05-22T00:02:27.050430Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T00:02:27.050430Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.21499","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":"2026-05-22T00:02:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SQgphOu4wuInLt4/5bZeMsNPeKQr2M5UYcquKbYb1hbEjVsEuy3SFFbCX+DjRTEYJP2DZ3LZK7+I/13EDaNiAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-19T22:50:18.074734Z"},"content_sha256":"c866b6386e1ee4050b1c4afcd48544a7193b96b9830dc5e59f9156516631fadf","schema_version":"1.0","event_id":"sha256:c866b6386e1ee4050b1c4afcd48544a7193b96b9830dc5e59f9156516631fadf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:GXL467GWBKZER2TURI7EMGXG75","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Conditional Neural Field based Reduced Order Model for Dynamic Ditching Load Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"physics.flu-dyn","authors_text":"Henning Schwarz, Jens-Peter M. Zemke, Pyei Phyo Lin, Thomas Rung","submitted_at":"2026-05-05T16:03:58Z","abstract_excerpt":"Grid-based neural networks such as convolutional autoencoders are widely used in dimension reduction-based surrogate models for computational fluid dynamics. In recent years, the use of coordinate-based approaches like conditional neural fields has emerged. Their independence of the spatial discretization is a beneficial feature for various applications in computational fluid dynamics. This paper discusses the spatio-temporal prediction of aircraft ditching loads using a conditional neural field approach. The model is evaluated using two datasets for the dynamic loads of the fuselage of a DLR-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.21499","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/2605.21499/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":"2026-05-22T00:02:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"We62Qffoa5GHl137kOAnnQpfR7JqVaJYOnpOn1EQgEV4I6EC8PyYL69hH9j9DbfhUnfOKk7h4ssP5VScsgWSBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-19T22:50:18.075112Z"},"content_sha256":"4ab4e7d72d17e2dff1ae5b51b5f5cfe0f2d6b284caaa616eada65a6aee5267d9","schema_version":"1.0","event_id":"sha256:4ab4e7d72d17e2dff1ae5b51b5f5cfe0f2d6b284caaa616eada65a6aee5267d9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GXL467GWBKZER2TURI7EMGXG75/bundle.json","state_url":"https://pith.science/pith/GXL467GWBKZER2TURI7EMGXG75/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GXL467GWBKZER2TURI7EMGXG75/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":"2026-06-19T22:50:18Z","links":{"resolver":"https://pith.science/pith/GXL467GWBKZER2TURI7EMGXG75","bundle":"https://pith.science/pith/GXL467GWBKZER2TURI7EMGXG75/bundle.json","state":"https://pith.science/pith/GXL467GWBKZER2TURI7EMGXG75/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GXL467GWBKZER2TURI7EMGXG75/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:GXL467GWBKZER2TURI7EMGXG75","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":"efe176f3b751ab95199008d56a091c83d5861279c43210ef210bd3782c4bb6d1","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-05T16:03:58Z","title_canon_sha256":"075f0b74226981ee73aa3cd1f3c81b821140b9e0bf8b7ca4cc2e4fe437fdaf69"},"schema_version":"1.0","source":{"id":"2605.21499","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.21499","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"arxiv_version","alias_value":"2605.21499v1","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.21499","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"pith_short_12","alias_value":"GXL467GWBKZE","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"pith_short_16","alias_value":"GXL467GWBKZER2TU","created_at":"2026-05-22T00:02:27Z"},{"alias_kind":"pith_short_8","alias_value":"GXL467GW","created_at":"2026-05-22T00:02:27Z"}],"graph_snapshots":[{"event_id":"sha256:4ab4e7d72d17e2dff1ae5b51b5f5cfe0f2d6b284caaa616eada65a6aee5267d9","target":"graph","created_at":"2026-05-22T00:02:27Z","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/2605.21499/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Grid-based neural networks such as convolutional autoencoders are widely used in dimension reduction-based surrogate models for computational fluid dynamics. In recent years, the use of coordinate-based approaches like conditional neural fields has emerged. Their independence of the spatial discretization is a beneficial feature for various applications in computational fluid dynamics. This paper discusses the spatio-temporal prediction of aircraft ditching loads using a conditional neural field approach. The model is evaluated using two datasets for the dynamic loads of the fuselage of a DLR-","authors_text":"Henning Schwarz, Jens-Peter M. Zemke, Pyei Phyo Lin, Thomas Rung","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-05T16:03:58Z","title":"Conditional Neural Field based Reduced Order Model for Dynamic Ditching Load Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.21499","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:c866b6386e1ee4050b1c4afcd48544a7193b96b9830dc5e59f9156516631fadf","target":"record","created_at":"2026-05-22T00:02:27Z","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":"efe176f3b751ab95199008d56a091c83d5861279c43210ef210bd3782c4bb6d1","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-05T16:03:58Z","title_canon_sha256":"075f0b74226981ee73aa3cd1f3c81b821140b9e0bf8b7ca4cc2e4fe437fdaf69"},"schema_version":"1.0","source":{"id":"2605.21499","kind":"arxiv","version":1}},"canonical_sha256":"35d7cf7cd60ab248ea748a3e461ae6ff4b1f29fb6937a08c054f172a6bd3cffa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"35d7cf7cd60ab248ea748a3e461ae6ff4b1f29fb6937a08c054f172a6bd3cffa","first_computed_at":"2026-05-22T00:02:27.050430Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-22T00:02:27.050430Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3HKzogMmRA/MOauOeOnDsbLfIHkHPjYEXpeIOQl9Tg6sYVr+FBpPP/Uiv6YMgH0EmvXWrf/NgLQ/MtPXncxDDA==","signature_status":"signed_v1","signed_at":"2026-05-22T00:02:27.050961Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.21499","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c866b6386e1ee4050b1c4afcd48544a7193b96b9830dc5e59f9156516631fadf","sha256:4ab4e7d72d17e2dff1ae5b51b5f5cfe0f2d6b284caaa616eada65a6aee5267d9"],"state_sha256":"707820dfbf33ba012d4c1a9c425f1e2808d0c6c6322cf295c82c103cf1594591"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oon3+X/HpO+Rt2/VDrNB1eKdRLSFh/5T16gloM8Dx/2bPbQnpiLyVklaIYIp5wgddDmwyrbWLAJ2gHGPPcvYAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-19T22:50:18.077166Z","bundle_sha256":"d72444661aa20fee4e193c5746b6c3cee2177e46bb1d19d6a1a5766186265e60"}}