Michelson interferometer thermo-optic switch on SOI with a 50-μW power consumption
Bibliographic record
Abstract
We demonstrate photonic ultra-efficient thermo-optic switches on a 220-nm silicon-on-insulator platform. We used several approaches to increase the tuning efficiency of the switches. We used folded waveguides in a Michelson interferometer configuration to increase the optical interaction length of the light with the heated region, and used a suspended structure to improve thermal isolation. An ultra-low switching power of 50 μW is realized with an extinction ratio of over 26 dB for the transverse electric mode at 1550 nm. The 10%–90% response time of the switch is 1.28 ms, including a 780 μs rise time and a 500 μs fall time. Compared with the best thermo-optic switch in the literature, our device shows approximately an order of magnitude reduction in power consumption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".