Wideband dynamic microwave frequency identification system using a low-power ultracompact silicon photonic chip
Bibliographic record
Abstract
Photonic-based instantaneous frequency measurement (IFM) of unknown microwave signals offers improved flexibility and frequency range as compared with electronic solutions. However, no photonic platform has ever demonstrated the key capability to perform dynamic IFM, as required in real-world applications. In addition, all demonstrations to date employ bulky components or need high optical power for operation. Here we demonstrate an integrated photonic IFM system that can identify frequency-varying signals in a dynamic manner, without any need for fast measurement instrumentation. The system is based on a fully linear, ultracompact system based on a waveguide Bragg grating on silicon, only 65-μm long and operating up to ∼30 GHz with carrier power below 10 mW, significantly outperforming present technologies. These results open a solid path towards identification of dynamically changing signals over tens of GHz bandwidths using a practical, low-cost on-chip implementation for applications from broadband communications to biomedical, astronomy and more.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".