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Record W4404810066 · doi:10.1109/jlt.2024.3507941

Power-Efficient Silicon Photonic Thermo-Optic Switch Covering OESCLU-Bands Enabled by Mode-Looped Phase Shifters With Subwavelength Gratings

2024· article· en· W4404810066 on OpenAlexaff
Weijia Li, Luhua Xu, D. Kim Turgeon, Zixian Wei, Jinsong Zhang, Charles St-Arnault, Wei Shi, David V. Plant

Bibliographic record

VenueJournal of Lightwave Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsCMC Microsystems (Canada)McGill University
Fundersnot available
KeywordsOptoelectronicsMaterials scienceSiliconSilicon photonicsPhotonicsOpticsPhase (matter)Integrated opticsPhotonic integrated circuitPhotonic crystalPower (physics)Physics

Abstract

fetched live from OpenAlex

Ultra-broadband wavelength division multiplexing (WDM) optical networks with densely populated nodes are emerging as a principal direction for enhancing future capacity and advancing network evolution. To address this growing demand, we have developed a colorless, power-efficient thermo-optic Mach-Zehnder switch (MZS) utilizing mode-looped phase shifters. This phase shifter doubles the tuning efficiency by recirculating light through the heated region twice. The phase shifter is optimized to ensure a balanced performance across all optical communication bands, including O-, E-, S-, C-, L-, and U-bands. Furthermore, we have incorporated subwavelength grating structures (SWGs) into the adiabatic 3-dB couplers and dual-mode (de)multiplexers, which are critical for enhancing the ultra-broadband capabilities of the MZS. Experimental results demonstrate that our device achieves a switching power of 11.15 mW, with extinction ratios (ERs) surpassing 8.44 dB over a 405-nm wavelength range, and exceeding 10 dB from 1295 nm to 1675 nm. These capabilities establish our switch as a key component for future multi-band and power-efficient reconfigurable add-drop optical networks (ROADMs), with the potential to advance the telecommunications industry by supporting expanded bandwidths and enhanced efficiency.

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 categoriesMeta-epidemiology (narrow)
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 score0.360
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.004
GPT teacher head0.223
Teacher spread0.219 · 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.

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

Citations3
Published2024
Admission routes1
Has abstractyes

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