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Record W2754570455 · doi:10.1063/1.5004561

Noise spectra in balanced optical detectors based on transimpedance amplifiers

2017· article· en· W2754570455 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

VenueReview of Scientific Instruments · 2017
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsUniversity of Calgary
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsTransimpedance amplifierShot noiseNoise (video)Bandwidth (computing)DetectorPhotodiodeNoise powerNoise generatorPhysicsEffective input noise temperatureOperational amplifierElectronic engineeringAmplifierComputer scienceElectrical engineeringLow-noise amplifierOpticsPower (physics)Noise figureTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

We present a thorough theoretical analysis and experimental study of the shot and electronic noise spectra of a balanced optical detector based on an operational amplifier connected in a transimpedance scheme. We identify and quantify the primary parameters responsible for the limitations of the circuit, in particular, the bandwidth and shot-to-electronic noise clearance. We find that the shot noise spectrum can be made consistent with the second-order Butterworth filter, while the electronic noise grows linearly with the second power of the frequency. Good agreement between the theory and experiment is observed; however, the capacitances of the operational amplifier input and the photodiodes appear significantly higher than those specified in manufacturers' datasheets. This observation is confirmed by independent tests.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.918

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 science0.0010.000
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 head0.018
GPT teacher head0.300
Teacher spread0.282 · 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