Single‐Shot Ultraviolet Compressed Ultrafast Photography
Bibliographic record
Abstract
Abstract Compressed ultrafast photography (CUP) is an emerging potent technique that allows imaging a nonrepeatable or difficult‐to‐produce transient event in a single shot. Despite many recent advances, existing CUP techniques operate only at visible and near‐infrared wavelengths. In addition, spatial encoding via a digital micromirror device (DMD) in CUP systems often limits its field of view and imaging speeds. Finally, conventional reconstruction algorithms have limited control of the reconstruction process to further improve the image quality in the recovered datacubes of the scene. To overcome these limitations, this article reports a single‐shot UV‐CUP that exhibits a sequence depth of up to 1500 frames with a size of 1750 × 500 pixels at an imaging speed of 0.5 trillion frames per second. A patterned photocathode is integrated into a streak camera, which overcomes the previous restrictions in DMD‐based spatial encoding and improves the system's compactness. Meanwhile, the plug‐and‐play alternating direction method of multipliers algorithm is implemented to CUP's image reconstruction to enhance reconstructed image quality. UV‐CUP's single‐shot ultrafast imaging ability is demonstrated by recording UV pulses transmitting through various spatial patterns. UV‐CUP is expected to find many applications in both fundamental and applied science.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".