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Record W2136575352 · doi:10.1109/jlt.2005.843840

Tunable passive all-optical pulse repetition rate multiplier using fiber Bragg gratings

2005· article· en· W2136575352 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.

Bibliographic record

VenueJournal of Lightwave Technology · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsTalbot effectFiber Bragg gratingJitterOpticsMultiplier (economics)RipplePulse waveCascadePhysicsOptical fiberMaterials scienceComputer scienceGratingLaserTelecommunicationsVoltageEngineering

Abstract

fetched live from OpenAlex

We demonstrate a tunable passive all-optical pulse repetition rate multiplier based on the fractional temporal Talbot effect. The multiplier comprises a series of identical linearly chirped fiber Bragg gratings (LCFBGs) interconnected via two multiport (N/spl times/N) switches. Discrete multiplication factors are obtained by simply using the switch to set the optical path of the input pulse train to be reflected by the required number of gratings, and hence, corresponding dispersion, to satisfy the Talbot condition. In our demonstration, we reflect an 8.62-GHz input pulse train from a cascade of one to four LCFBGs, resulting in discrete repetition rate multiplication factors of 12, 6, 4, and 3, respectively. We obtain output repetition rates exceeding 100 GHz; the multiplied train exhibits excellent signal stability with low amplitude ripple and timing jitter, and the output pulses are of similar duration to those at the input.

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 score0.290
Threshold uncertainty score0.665

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 integrity0.0000.001
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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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