High-spatial-resolution ultrafast framing imaging at 15 trillion frames per second by optical parametric amplification
Bibliographic record
Abstract
We report a framing imaging based on noncollinear optical parametric amplification (NCOPA), named FINCOPA, which applies NCOPA for the first time to single-shot ultrafast optical imaging. In an experiment targeting a laser-induced air plasma grating, FINCOPA achieved 50 fs-resolved optical imaging with a spatial resolution of ∼83 lp / mm and an effective frame rate of 10 trillion frames per second (Tfps). It has also successfully visualized an ultrafast rotating optical field with an effective frame rate of 15 Tfps. FINCOPA has simultaneously a femtosecond-level temporal resolution and frame interval and a micrometer-level spatial resolution. Combining outstanding spatial and temporal resolutions with an ultrahigh frame rate, FINCOPA will contribute to high-spatiotemporal resolution observations of ultrafast transient events, such as atomic or molecular dynamics in photonic materials, plasma physics, and laser inertial-confinement fusion.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".