Silicon Photonic Integrated Optoelectronic Oscillator for Frequency-Tunable Microwave Generation
Bibliographic record
Abstract
Photonic generation of a frequency-tunable microwave signal based on a silicon photonic integrated optoelectronic oscillator (OEO) is proposed and experimentally demonstrated. The silicon photonic chip includes a high-speed phase modulator (PM), a thermally tunable micro-disk resonator (MDR), and a high-speed photodetector (PD). When an external light wave is injected into the chip, by a joint use of the PM, the MDR, and the PD, a bandpass microwave photonic filter (MPF) based on phase modulation and phase-modulation to intensity-modulation (PM-IM) conversion is realized. If the output microwave signal from the MPF is fed to the microwave input port of the PM with a sufficiently large gain provided by an electrical amplifier, the MPF becomes an OEO. By controlling the electrical power applied to a micro-heater, the resonance frequency of the MDR is tuned, which leads to the tuning of the MPF, and thus, the OEO oscillation frequency. In the experimental demonstration, two silicon photonic integrated OEOs using two MDRs with different micro-heaters are studied. The first OEO has a high-resistivity metallic micro-heater placed on top of the MDR, and the second OEO has a p-type doped silicon heater in the MDR. The two thermally tunable MDRs are characterized, and the performance of the MPFs based on the two MDRs is evaluated. The use of the two MPFs to implement two OEOs is performed, and their performance is evaluated in terms of frequency tunable range, phase noise, and power consumption.
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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".