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Record W4396982361 · doi:10.1109/jlt.2024.3401773

High-Bandwidth Silicon Traveling-Wave Modulator Using Distributed Micro-Capacitors

2024· article· en· W4396982361 on OpenAlexfundno aff
Abdolkhalegh Mohammadi, Arman Safarnejadian, Zibo Zheng, Ming Zeng, Leslie A. Rusch, Wei Shi

Bibliographic record

VenueJournal of Lightwave Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCapacitorBandwidth (computing)Traveling waveSiliconMaterials scienceOptoelectronicsElectrical engineeringPhase modulationElectronic engineeringOpticsPhysicsEngineeringVoltageTelecommunicationsPhase noise

Abstract

fetched live from OpenAlex

We introduce a bandwidth enhancement technique for traveling-wave Mach-Zehnder modulators (TW-MZM). This approach reduces the microwave attenuation caused by the loaded PN junction capacitance. We achieved a bandwidth of 61 GHz for a 4-mm long silicon modulator, significantly greater than the 45 GHz bandwidth of a conventional design, while maintaining a comparable V<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_\pi$</tex-math></inline-formula>. Conducted simulations and circuit analysis demonstrated the efficacy of the proposed approach. We also compared the performance of our solution with the reference modulator experimentally in transmission tests at various baud rates. The proposed micro-capacitor-enhanced TW-MZM has a lower bit error rate and can reach up to 120 Gbaud while respecting the bit error rate threshold for forward error correction with a 7% overhead.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

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