Discretely tunable comb spacing of a frequency comb by multilevel phase modulation of a periodic pulse train
Bibliographic record
Abstract
We experimentally demonstrate tunable comb spacing of an original 10-GHz periodic frequency comb by spectral Talbot effect over an unprecedented range of even and odd comb spacing division factors, from 2 to 9. The implementation has been achieved by periodic electro-optic (EO) temporal phase modulation of the original comb (conventional mode-locked optical pulse train) with multilevel modulation functions, produced by an arbitrary waveform generator (AWG). These comb spacing division processes have been observed through the use of a high-resolution (20-MHz) optical spectrum analyzer. Comb spacing tuning is achieved without essentially affecting the spectral bandwidth and total energy of the original comb signal. Our results also confirm that the spectral Talbot method does not require carrier-envelope phase stabilization in the input frequency comb. Numerical studies on the impact of deviations in the applied phase modulation functions confirm the robustness of the technique, in agreement with the experimental results.
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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".