Dispersion measurement assisted by a stimulated parametric process
Bibliographic record
Abstract
Dispersion plays a major role in the behavior of light inside photonic devices. Current state-of-the-art dispersion measurement techniques utilize linear interferometers that can be applied to devices with small dispersion-length products. However, linear interferometry often requires beam alignment and phase stabilization. Recently, common-path nonlinear interferometers in the spontaneous regime have been used to demonstrate alignment-free and phase-stable dispersion measurements. However, they require single-photon detectors, resulting in high system cost and long integration times. We overcome these issues by utilizing a nonlinear interferometer in the stimulated regime and demonstrate the ability to measure the dispersion of a device with a dispersion-length product as small as 0.009 ps/nm at a precision of 0.0002 ps/nm. Moreover, this regime allows us to measure dispersion with shorter integration times (in comparison to the spontaneous regime) and conventional optical components and detectors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".