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Record W2167075232 · doi:10.1109/jlt.2003.814393

Simple and highly sensitive method for wavelength measurement of low-power time-multiplexed signals using optical amplifiers

2003· article· en· W2167075232 on OpenAlexaff
D.J.F. Cooper, P. W. Smith

Bibliographic record

VenueJournal of Lightwave Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOptical amplifierMultiplexingDuty cycleAmplified spontaneous emissionAmplifierSIGNAL (programming language)Wavelength-division multiplexingOpticsFilter (signal processing)Noise (video)Optical filterPhysicsWavelengthPower (physics)Computer scienceOptoelectronicsTelecommunicationsElectrical engineeringEngineeringLaserCMOS

Abstract

fetched live from OpenAlex

We describe a simple method for the wavelength measurement of optical signals that is easily capable of measuring a 1-nW average power optical signal with a wavelength resolution of 0.1 pm/Hz <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> 2/ while maintaining a large measurement range in excess of 12 nm. The system uses an erbium-doped fiber amplifier to increase the signal level before being measured with a wide-band edge filter. This technique is well suited to the measurement of low duty cycle time-multiplexed signals such as those in multiplexed fiber sensor systems. We show that the measurement of the amplified signal is improved despite the broadband nature of the amplified spontaneous emission noise. We show for the first time that the addition of an amplifier can increase the detection capabilities of the edge filter method beyond the shot noise limit of an unamplified measurement.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.243
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.019
GPT teacher head0.267
Teacher spread0.249 · 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 designBench or experimental
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

Citations12
Published2003
Admission routes1
Has abstractyes

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