2×2 MMI-MZI GaAs-GaAlAs carrier-injection optical switch
Bibliographic record
Abstract
The refractive index change induced by carrier-injection in III-V semiconductors, such as GaAs-GaAlAs, can be used to fabricate fast optical switches with a switching speed in the nanosecond range. These fast optical switches have important applications in advanced optical networks, such as optical packet-switching, network provisioning/reconfiguration, fault restoration, etc. Most of the carrier-injection switches reported have been based on the carrier-induced Total Internal Reflection (TIR). Although such TIR carrier-injection switches have the attractive feature of compact size for high monolithic integration density, the critical challenges in fabricating these devices include the electrode fabrication complexity and the small fabrication tolerance. Also, a high injected current larger than 100 mA is usually required to achieve the TIR and hence the realization of low power consumption has become a significant issue. To overcome these serious problems, a Mach-Zehnder Interferometer (MZI) can be employed to implement carrier-injection switches. In an MZI-based switch, the two MZI arms are formed by two identical single-mode waveguides with electrodes, fabricated on the top of the waveguides, which allow variation of the phase difference between them, based on the carrier-injection effect. Compared to the TIR switches, the advantages of these MZI-based switches include simple electrode fabrication, ease of fabrication tolerance, and high on-off extinction ratio. More importantly, the injected current required to achieve π phase difference between the MZI arms is much smaller than that to achieve TIR, and therefore the power consumption of the MZI switches is much lower than that of the TIR devices. In this paper, we present a 2×2 GaAs-GaAlAs carrier-injection switch based on an MZI formed by two Multi-Mode Interference (MMI) couplers. Such an optical switch has a low insertion loss, high on-off extinction ratio, and very low power consumption. This device has important applications for the future optical Green Internet.
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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) | 0.001 | 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; 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".