Low-current optical switching by carrier-injection-induced reconfigurable waveguiding
Bibliographic record
Abstract
Progress in optical switching technology currently faces several major obstacles. One of these is high power consumption, which quickly multiplies in cascaded switch configurations. As well, many implementations have long switching speeds and large footprints. An improved compact 1x2 digital optical switch (DOS) in InGaAsP/InP is presented, with experimental results compared to numerical modeling. The Y-junction waveguide switch operation is based on reconfiguration of output waveguide arms by carrier injection at the electrodes. We present experimental results of DOS fabricated with InGaAsP cores having bandgaps of 1.2um, 1.3um, and 1.4um. The results are compared with calculations of refractive index change versus carrier concentration in the different InGaAsP alloys. Additionally, wafer layer structure and waveguide parameters were redesigned to decrease, respectively, power dissipation and optical confinement. Switching current is significantly reduced from greater than 100 mA to about 20 mA, which not only provides power savings, but also results in less thermal overshoot in the switched optical pulse. The DOS has a measured switching contrast ratio of better than 12.5 dB, with a transition time of less than 5ns. Polarization dependence of switching contrast is also explored.
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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".