{"doi":"10.1364/ol.420737","title":"Compressed ultrafast tomographic imaging by passive spatiotemporal projections","abstract":"Existing streak-camera-based two-dimensional (2D) ultrafast imaging techniques are limited by long acquisition time, the trade-off between spatial and temporal resolutions, and a reduced field of view. They also require additional components, customization, or active illumination. Here we develop compressed ultrafast tomographic imaging (CUTI), which passively records 2D transient events with a standard streak camera. By grafting the concept of computed tomography to the spatiotemporal domain, the operations of temporal shearing and spatiotemporal integration in a streak camera’s data acquisition can be equivalently expressed as the spatiotemporal projection of an <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"> <mml:mo stretchy=\"false\">(</mml:mo> <mml:mi>x</mml:mi> <mml:mo>,</mml:mo> <mml:mi>y</mml:mi> <mml:mo>,</mml:mo> <mml:mi>t</mml:mi> <mml:mo stretchy=\"false\">)</mml:mo> </mml:math> datacube from a certain angle. Aided by a new, to the best of our knowledge, compressed-sensing reconstruction algorithm, the 2D transient event can be accurately recovered in a few measurements. CUTI is exhibited as a new imaging mode universally adaptable to most streak cameras. Implemented in an image-converter streak camera, CUTI captures the sequential arrival of two spatially modulated ultrashort ultraviolet laser pulses at 0.5 trillion frames per second. Applied to a rotating-mirror streak camera, CUTI records an amination of fast-bouncing balls at 5,000 frames per second.","journal":"Optics Letters","year":2021,"id":177134,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":20,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9594,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":664138,"name":"Ruibo Shang","orcid":null,"position":1,"is_corresponding":false},{"id":721376,"name":"C. Y. Côté","orcid":null,"position":2,"is_corresponding":false},{"id":540774,"name":"Xianglei Liu","orcid":"0000-0001-5647-5206","position":3,"is_corresponding":false},{"id":721377,"name":"Antoine Laramée","orcid":null,"position":4,"is_corresponding":false},{"id":720708,"name":"François Légaré","orcid":"0000-0002-3065-7156","position":5,"is_corresponding":false},{"id":453102,"name":"Geoffrey P. Luke","orcid":"0000-0002-1486-3398","position":6,"is_corresponding":false},{"id":253574,"name":"Jinyang Liang","orcid":"0000-0001-5983-0488","position":7,"is_corresponding":false},{"id":720707,"name":"Yingming Lai","orcid":"0009-0003-6982-5676","position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":null,"created_at":"2026-07-18T23:47:28.018172Z","pmid":"33793544","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}