Analysis, optimization, and spice modeling of resonant cavity enhanced p-i-n photodetector
Bibliographic record
Abstract
We present a detailed analysis, optimization, and SPICE modeling of the resonant-cavity-enhanced p-i-n photodetector (RCE-p-i-n-PD). Time response, frequency response, and the quality factor of RCE-p-i-n-PD are calculated for different thicknesses of the active layer and for different areas of the photodetector. The standing-wave effect is examined for all these calculations. The effect of the parasitic inductor is studied, and then an optimization is applied to the photodetector to get the optimal value of thickness of the active layer and the series inductor values. Two cases are compared, one with an inductor (L) in series with the load resistor (R/sub L/), and another without this inductor. High performance is obtained in the first case with an inductor, and its optimal values are obtained. A SPICE model for this high-speed photodetector is also presented, and the transfer function of this model is compared for different parameters of the device. Finally, predictions from this SPICE model are compared with published experimental results.
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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 | 0.001 |
| 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".