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Record W3009722799 · doi:10.1109/lpt.2020.2978793

Mach-Zehnder Silicon Photonic Modulator Assisted by Phase-Shifted Bragg Gratings

2020· article· en· W3009722799 on OpenAlexafffund
Omid Jafari, Wei Shi, Sophie LaRochelle

Bibliographic record

VenueIEEE Photonics Technology Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversité Laval
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsMaterials scienceSilicon photonicsBandwidth (computing)OptoelectronicsResonatorSilicon on insulatorPhase modulationPhotonicsOpticsFiber Bragg gratingModulation (music)SiliconPhysicsTelecommunicationsComputer sciencePhase noiseWavelength

Abstract

fetched live from OpenAlex

We experimentally demonstrate a silicon photonic Mach-Zehnder modulator (MZM) assisted by phase-shifted Bragg gratings. Coupled resonators are inserted in the Bragg grating structure to significantly enhance the phase modulation efficiency, while maintaining a wide optical bandwidth compared to other resonator-based modulators. Fabricated using a CMOS-compatible foundry process, the device achieved a small-signal Vπ× L of 0.18 V.cm, which is seven times lower than a conventional silicon MZM fabricated with the same process. The device has a compact footprint, with a length of only 162 μm, and shows a modulation bandwidth of 28 GHz at a reverse bias of 1 V. Non-return-to-zero modulation is demonstrated at 30 Gb/s with a bit-error-rate (BER) below the 7%-overhead forward error correction (FEC) threshold over a bandwidth of 3.5 nm. This bandwidth should translate into an operating temperature range greater than 40 °C.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations49
Published2020
Admission routes2
Has abstractyes

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