Invited Article: Electrically tunable silicon-based on-chip microdisk resonator for integrated microwave photonic applications
Bibliographic record
Abstract
Silicon photonics with advantages of small footprint, compatibility with the mature CMOS fabrication technology, and its potential for seamless integration with electronics is making a significant difference in realizing on-chip integration of photonic systems. A microdisk resonator (MDR) with a strong capacity in trapping and storing photons is a versatile element in photonic integrated circuits. Thanks to the large index contrast, a silicon-based MDR with an ultra-compact footprint has a great potential for large-scale and high-density integrations. However, the existence of multiple whispering gallery modes (WGMs) and resonance splitting in an MDR imposes inherent limitations on its widespread applications. In addition, the waveguide structure of an MDR is incompatible with that of a lateral PN junction, which leads to the deprivation of its electrical tunability. To circumvent these limitations, in this paper we propose a novel design of a silicon-based MDR by introducing a specifically designed slab waveguide to surround the disk and the lateral sides of the bus waveguide to suppress higher-order WGMs and to support the incorporation of a lateral PN junction for electrical tunability. An MDR based on the proposed design is fabricated and its optical performance is evaluated. The fabricated MDR exhibits single-mode operation with a free spectral range of 28.85 nm. Its electrical tunability is also demonstrated and an electro-optic frequency response with a 3-dB modulation bandwidth of ∼30.5 GHz is measured. The use of the fabricated MDR for the implementation of an electrically tunable optical delay-line and a tunable fractional-order temporal photonic differentiator 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".