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Record W1967300931 · doi:10.1364/ol.39.000701

Tunable nanophotonic delay lines using linearly chirped contradirectional couplers with uniform Bragg gratings

2014· article· en· W1967300931 on OpenAlexaff
Wei Shi, Venkat Veerasubramanian, David Patel, David V. Plant

Bibliographic record

VenueOptics Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcGill University
Fundersnot available
KeywordsOpticsOptical circulatorFiber Bragg gratingMaterials scienceExtinction ratioGroup delay and phase delayTaperingInsertion lossOptoelectronicsPhysicsOptical fiberBandwidth (computing)WavelengthTelecommunications

Abstract

fetched live from OpenAlex

We demonstrate an integrated tunable optical delay line in grating-assisted contradirectional couplers using a CMOS-compatible photonic technology. The input signal is delayed through dispersive Bragg gratings and distributedly coupled to the drop port of the coupler without backreflections. This add-drop design enables monolithic integration of grating-based delay lines without using optical circulators. The gratings are formed by slab perturbations in rib waveguides, with the index chirping realized by linearly tapering the rib widths. Both the pitch and size of the gratings are constant through the entire coupler, for a higher tolerance to fabrication errors. Continuous tuning of the optical group delay of up to 96 ps has been obtained, with a low insertion loss of less than 2 dB and a negative chromatic dispersion of -11 ps/nm that allows for bit rates of up to almost 100 Gb/s at the maximal delay. The device has a small footprint of 0.015 mm2, and can be used for on-chip optical buffering, dispersion compensation, and pulse compression.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.842

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)0.0000.000

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 head0.007
GPT teacher head0.188
Teacher spread0.181 · 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 designSimulation or modeling
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

Citations59
Published2014
Admission routes1
Has abstractyes

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