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Record W4391213625 · doi:10.1117/12.3000184

On-chip electro-optic modulator based on left-handed photonic crystals

2024· article· en· W4391213625 on OpenAlexaff
Yalın Başay, Onur Akdeniz, Alperen Gövdeli, Cenk Yanık, Süleyman Çelik, Serdar Kocaman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLeft handedPhotonicsChipOptoelectronicsElectro-optic modulatorOpticsPhotonic crystalPhysicsMaterials scienceComputer scienceOptical modulatorPhase modulationTelecommunications

Abstract

fetched live from OpenAlex

To achieve more compact integrated photonic devices, reducing size of elements is crucial. A factor that limits sizereduction is electro-optic components that require large optical interaction length. In this work, we designed and fabricated an optical modulator where a photonic crystal structure is used to create large phase difference in short distance. Our design is a 2x2 Mach-Zehnder interferometer on the platform of silicon-on-insulator. A left-handed photonic crystal structure that is designed to operate at 1.55 um is placed on one arm of the interferometer to add phase to light. The phase difference between two arms yields amplitude modulation at the output of the interferometer. The photonic crystal is hexagonal air hole lattice and used to switch between negative and positive effective refractive indices. This change is triggered by applying voltage which decreases the refractive index of silicon from 3.480 to 3.477 due to plasma dispersion effect, and causes photonic band-to-band transition. By this way, effective refractive index of the structure jumps from negative to positive values. To be able to realize this, photonic crystal region is sandwiched between n-doped and p-doped materials, which creates a p-i-n diode. By taking the advantage of band-to-band transition at left-handed photonic crystal, we experimentally demonstrated that interaction length is reduced from 255 um to 4.4 um. This reduction leads to low optical insertion loss as well as more compact devices.

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 score0.001
Threshold uncertainty score0.004

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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