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Record W2155373087 · doi:10.1109/ted.2005.843885

Effects of the Parasitics on the Time Response of RCE-PDs

2005· article· en· W2155373087 on OpenAlexaff
Yasser M. El-Batawy, M. Jamal Deen

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2005
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsParasitic extractionPhotodetectorInductorResistorOptoelectronicsElectronic engineeringCapacitive sensingMaterials scienceElectrical engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

Resonant cavity enhanced photodetectors (RCE-PDs) are promising candidates for applications in high-speed optical communications and interconnections. However, because parasitics effects of these high-speed photodetectors can significantly degrade the performance of the photodetector, then they must be carefully considered. Here, an accurate model for the time response of the RCE-PDs that includes the effects of their parasitics is presented. The effects of an inductor that may be added in series with the load resistor are also studied and it is shown that the external inductor can improve the performance of the photodetector because it compensates some of the degradations resulting from capacitive parasitics. The effects of the parasitics have been investigated for different dimensions of the photodetectors, different values of both the load resistance and the added inductor and also for different multiplication gains for the case of RCE-avalanche photodetectors.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.004
GPT teacher head0.208
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 source (direct Gemma or distilled Codex), 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

Citations10
Published2005
Admission routes1
Has abstractyes

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