Phase retrieval approach for an accurate reconstruction of an arbitrary optical waveform in the petahertz optical oscilloscope
Bibliographic record
Abstract
Abstract An arbitrary optical waveform can be measured using the technique called the ‘petahertz optical oscilloscope’ in which an electron trajectory in the process of high harmonic generation is used as a fast temporal gate. In the petahertz optical oscilloscope, a signal laser pulse that needs to be measured is superposed on a fundamental laser pulse that generates high harmonic radiation. The addition of the signal laser pulse slightly modifies the amplitude and phase of the harmonic radiation, which have information on the signal field. While these changes are imposed in the generation medium, the harmonic radiation is measured at the detector. Thus, one needs a special technique to find the phase modulation in the medium using the variation of the spatially-resolved harmonic spectrum measured at the far field. We find that a simple estimation using the deflection angle of the harmonic radiation is not accurate enough for a broadband signal pulse. Here we introduce a phase retrieval approach for the reconstruction of the broadband signal pulse. Our calculations show that the broadband signal pulse can be accurately reconstructed using the phase retrieval approach.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".