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Record W2541595513 · doi:10.1109/issse.1998.738063

Broad-band low-noise preamplifier design with GaAs MESFETs for optical communication systems

2002· article· en· W2541595513 on OpenAlexaff
A. Boyogueno Bende, Bożena Kamińska

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTransimpedance amplifierPreamplifierBandwidth (computing)PhotodiodeCapacitanceOptoelectronicsElectronic engineeringElectrical engineeringCommon emitterComputer scienceOptical communicationPhysicsEngineeringOperational amplifierTelecommunicationsAmplifier

Abstract

fetched live from OpenAlex

Classical designs of transimpedance preamplifiers for optical receiver circuits use common-emitter (C-E) or common-source (C-S) input stages. The use of current-mode techniques to design photoreceivers for optical communication systems has been shown to offer significant bandwidth advantages over traditional voltage-mode designs. In this paper, we focus on the design of a wide-band, low-noise photoreceiver in GaAs using current-based amplifying techniques. A 3 dB bandwidth exceeding 3.5 GHz and, 48 dB of gain, along with 12pA//spl radic/(Hz) input noise have been simulated with a photodiode of 350 fF equivalent capacitance. Analysis of simulation results are presented, and a prototype has been sent for fabrication in the TQTRx 0.6 /spl mu/m process from TriQuint Semiconductor's technology.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.209
Teacher spread0.177 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2002
Admission routes1
Has abstractyes

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