Time-stretched sampling of a fast microwave waveform based on the repetitive use of a linearly chirped fiber Bragg grating in a dispersive loop
Bibliographic record
Abstract
Conventional sampling techniques may not be able to meet the ever-increasing demand for increased bandwidth from modern communications and radar signals. Optical time-stretched sampling has been considered an effective solution for wideband microwave signal processing. Here, we demonstrate a significantly increased stretching factor in the photonic time-stretched sampling of a fast microwave waveform. The microwave waveform to be sampled is intensity modulated on a chirped optical pulse generated jointly by a mode-locked laser and a length of dispersion compensating fiber. The pulse is then injected into an optical dispersive loop that includes an erbium-doped fiber amplifier and is stretched by a linearly chirped fiber Bragg grating multiple times in the loop. A record stretching factor of 36 is achieved based on an equivalent group delay dispersion coefficient of 12,000 ps/nm. This result could help address the new challenges imposed on signal processors to operate at a very high sampling rate.
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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) | 0.000 | 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".