Analysis, circuit modeling, and optimization of mushroom waveguide photodetector (mushroom-WGPD)
Bibliographic record
Abstract
The waveguide photodetector (WGPD) is considered a leading candidate to overcome the bandwidth/quantum-efficiency tradeoff in conventional photodetectors (PDs). To overcome the tradeoff between the capacitance and contact resistance, the mushroom-WGPD was proposed. A calibrated circuit model for mushroom-WGPD, including all parasitics, is presented so that a complete circuit simulation of the entire photoreceiver circuit with WGPD now becomes feasible. Both the behavior of the PD and its transfer function for the optical-to-electrical response that can be implemented in a circuit simulator are studied to explore the relationships between performance and design/ material parameters. The effects of the parasitics are also studied for different PD areas. The results from this circuit model of the PD have been compared with a published experimental work and a good agreement is obtained. In addition, the characteristics of mushroom-WGPD are studied for the case of an inductor added in series to the load resistor, and better performance is achieved in comparison to the case with no inductor. Based on the studies of different parameters for design and materials, optimization has been performed for the mushroom-WGPD. With this optimization, the optimal values of the thickness of the absorption layer and the added inductor to produce the highest bandwidth of the PD are obtained. These optimizations are performed for different areas of the PD and also for different load resistors, and they result in a significant improvement in the performance of the mushroom-WGPDs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".