{"paper":{"title":"A Bayesian approach to time-domain Photonic Doppler Velocimetry","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.data-an","physics.ins-det"],"primary_cat":"physics.plasm-ph","authors_text":"(2) Sandia National Laboratories, (3) Washington State University), A. Hansen (2) ((1) First Light Fusion Ltd., A. Porwitzky (2), B. Farfan (2), C. Johnson (2), D. Dolan (3), G. Burdiak (1), H. Doyle (1), J. R. Allison (1), J. Read (1), J. Skidmore (1), N. Hawker (1), N. Joiner (1), R. Bordas (1), T. Ao (2), V. Beltr\\'an (1)","submitted_at":"2025-08-19T09:55:49Z","abstract_excerpt":"Photonic Doppler Velocimetry (PDV) is an established technique for measuring the velocities of fast-moving surfaces in high-energy-density experiments. In the standard approach to PDV analysis, a short-time Fourier transform (STFT) is used to generate a spectrogram from which the velocity history of the target is inferred. The user chooses the form, duration and separation of the window function. Here we present a Bayesian approach to infer the velocity directly from the PDV oscilloscope trace, without using the spectrogram for analysis. This is clearly a difficult inference problem due to the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.13695","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/2508.13695/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"}