{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:GIQPF7Z2T3HGQZHKTJLSLFY35S","short_pith_number":"pith:GIQPF7Z2","schema_version":"1.0","canonical_sha256":"3220f2ff3a9ece6864ea9a5725971beca8832cfef2429d26e171044494dfcf17","source":{"kind":"arxiv","id":"2509.25924","version":4},"attestation_state":"computed","paper":{"title":"High Resolution and High-Speed Live Optical Flow Velocimetry","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.flu-dyn","authors_text":"Jean-Luc Aider, Juan Pimienta","submitted_at":"2025-09-30T08:20:46Z","abstract_excerpt":"Particle Image Velocimetry (PIV) typically relies on cross-correlation,which makes it difficult to obtain instantaneous velocity fields that are both spatially dense and available in real time at high acquisition rates. Optical Flow Velocimetry (OFV) offers a per-pixel alternative. Here we demonstrate real-tome OFV that delivers dense velocity fields (one vector per pixel) with high effective spatial resolution at frequencies up to the kHz range. Using synthetic particle images for two benchmarks -- a Rankine vortex and a homogeneous isotropic turbulence DNS -- we show that, with suitable part"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2509.25924","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2025-09-30T08:20:46Z","cross_cats_sorted":[],"title_canon_sha256":"daf5be84fc12f0747cdb773a7754ce6c33a1f646fd8f12e97f3ac3be07b4203e","abstract_canon_sha256":"9b7bf28db553e99a6bb46c150f9804443263ed4b10767f910e8d1f22b653ace6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T01:03:47.131204Z","signature_b64":"EKznEqS0yvJbuO7+ht72W52gqMfIA7/QNiZChTaqAnsQHXaLhYQYvVjYSlGgx2qxTOqXN/KfcFYp07x21JqTBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3220f2ff3a9ece6864ea9a5725971beca8832cfef2429d26e171044494dfcf17","last_reissued_at":"2026-05-22T01:03:47.130187Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T01:03:47.130187Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"High Resolution and High-Speed Live Optical Flow Velocimetry","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.flu-dyn","authors_text":"Jean-Luc Aider, Juan Pimienta","submitted_at":"2025-09-30T08:20:46Z","abstract_excerpt":"Particle Image Velocimetry (PIV) typically relies on cross-correlation,which makes it difficult to obtain instantaneous velocity fields that are both spatially dense and available in real time at high acquisition rates. Optical Flow Velocimetry (OFV) offers a per-pixel alternative. Here we demonstrate real-tome OFV that delivers dense velocity fields (one vector per pixel) with high effective spatial resolution at frequencies up to the kHz range. Using synthetic particle images for two benchmarks -- a Rankine vortex and a homogeneous isotropic turbulence DNS -- we show that, with suitable part"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.25924","kind":"arxiv","version":4},"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/2509.25924/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2509.25924","created_at":"2026-05-22T01:03:47.130339+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.25924v4","created_at":"2026-05-22T01:03:47.130339+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.25924","created_at":"2026-05-22T01:03:47.130339+00:00"},{"alias_kind":"pith_short_12","alias_value":"GIQPF7Z2T3HG","created_at":"2026-05-22T01:03:47.130339+00:00"},{"alias_kind":"pith_short_16","alias_value":"GIQPF7Z2T3HGQZHK","created_at":"2026-05-22T01:03:47.130339+00:00"},{"alias_kind":"pith_short_8","alias_value":"GIQPF7Z2","created_at":"2026-05-22T01:03:47.130339+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2605.04186","citing_title":"Real-Time Estimation of High-Resolution Flow Fields and Reduced-Order Coordinates from Event-Based Imaging Velocimetry","ref_index":73,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S","json":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S.json","graph_json":"https://pith.science/api/pith-number/GIQPF7Z2T3HGQZHKTJLSLFY35S/graph.json","events_json":"https://pith.science/api/pith-number/GIQPF7Z2T3HGQZHKTJLSLFY35S/events.json","paper":"https://pith.science/paper/GIQPF7Z2"},"agent_actions":{"view_html":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S","download_json":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S.json","view_paper":"https://pith.science/paper/GIQPF7Z2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.25924&json=true","fetch_graph":"https://pith.science/api/pith-number/GIQPF7Z2T3HGQZHKTJLSLFY35S/graph.json","fetch_events":"https://pith.science/api/pith-number/GIQPF7Z2T3HGQZHKTJLSLFY35S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S/action/storage_attestation","attest_author":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S/action/author_attestation","sign_citation":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S/action/citation_signature","submit_replication":"https://pith.science/pith/GIQPF7Z2T3HGQZHKTJLSLFY35S/action/replication_record"}},"created_at":"2026-05-22T01:03:47.130339+00:00","updated_at":"2026-05-22T01:03:47.130339+00:00"}