Recent Trends and Advances of Silicon-Based Integrated Microwave Photonics
Bibliographic record
Abstract
Multitude applications of photonic devices and technologies for the generation and manipulation of arbitrary and random microwave waveforms, at unprecedented processing speeds, have been proposed in the literature over the past three decades. This class of photonic applications for microwave engineering is known as microwave photonics (MWP). The vast capabilities of MWP have allowed the realization of key functionalities which are either highly complex or simply not possible in the microwave domain alone. Recently, this growing field has adopted the integrated photonics technologies to develop microwave photonic systems with enhanced robustness as well as with a significant reduction of size, cost, weight, and power consumption. In particular, silicon photonics technology is of great interest for this aim as it offers outstanding possibilities for integration of highly-complex active and passive photonic devices, permitting monolithic integration of MWP with high-speed silicon electronics. In this article, we present a review of recent work on MWP functions developed on the silicon platform. We particularly focus on newly reported designs for signal modulation, arbitrary waveform generation, filtering, true-time delay, phase shifting, beam steering, and frequency measurement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".