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Record W2141778962 · doi:10.1109/jlt.2003.816840

Analysis, optimization, and spice modeling of resonant cavity enhanced p-i-n photodetector

2003· article· en· W2141778962 on OpenAlexaff
Yasser M. El-Batawy, M. Jamal Deen, N. R. Das

Bibliographic record

VenueJournal of Lightwave Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSpicePhotodetectorInductorResistorEquivalent series resistanceEquivalent circuitRLC circuitMaterials scienceOptoelectronicsQ factorElectronic engineeringEngineeringElectrical engineeringVoltageCapacitor

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.210
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2003
Admission routes1
Has abstractyes

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