Microwave photonic integrator based on a multichannel fiber Bragg grating
Bibliographic record
Abstract
We propose and experimentally demonstrate a microwave photonic integrator based on a multichannel fiber Bragg grating (FBG) working in conjunction with a dispersion compensating fiber (DCF) to provide a step group delay response with no in-channel dispersion-related distortion. The multichannel FBG is designed based on the spectral Talbot effect, which provides a large group delay dispersion (GDD) within each channel. A step group delay response can then be achieved by cascading the multichannel FBG with a DCF having a GDD opposite the in-channel GDD. An optical comb, with each comb line located at the center of each channel of the FBG, is modulated by a microwave signal to be integrated. At the output of the DCF, multiple time-delayed replicas of the optical signal, with equal time delay spacing are obtained and are detected and summed at a photodetector (PD). The entire operation is equivalent to the integration of the input microwave signal. For a multichannel FBG with an in-channel GDD of 730 ps/nm and a DCF with an opposite GDD, an integrator with a bandwidth of 2.9 GHz and an integration time of 7 ns is demonstrated.
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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 | 0.001 | 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 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".