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Record W2132528324 · doi:10.1109/newcas.2012.6329049

A bandwidth enhancement technique for CMOS TIAs driven by large photodiodes

2012· article· en· W2132528324 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsTransimpedance amplifierPhotodiodeBandwidth (computing)CMOSCapacitanceOptoelectronicsRippleAmplifierElectronic engineeringComputer scienceMaterials scienceElectrical engineeringOperational amplifierPhysicsEngineeringTelecommunicationsVoltage

Abstract

fetched live from OpenAlex

A new method of enhancing the bandwidth of a conventional series-peaked transimpedance amplifier (TIA) driven by a large photodiode is introduced. It is shown that by using N identical TIAs in parallel the circuit bandwidth can be significantly improved. The advantage of the proposed technique is in its ability to provide large bandwidth enhancements in multi-GHz frequency ranges even when photodiode capacitance is large, without a noticeable increase in TIA core circuit area. This technique is supported by a design example simulated in a 0.13μm standard CMOS technology. Simulation results show a 3dB bandwidth of 26GHz with 0.5pF photodiode capacitance, a transimpedance gain of 51dBΩ and group delay of 33.5±4ps. The proposed technique shows an overall bandwidth enhancement ratio of 3.25 with less than 0.1dB gain ripple resulting in higher bandwidth enhancement than previously reported for large photodiode capacitances.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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