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Record W3111367118 · doi:10.1364/ol.410608

On-chip tunable microdisk laser fabricated on Er<sup>3+</sup>-doped lithium niobate on insulator

2020· article· lv· W3111367118 on OpenAlexafffund
Zhe Wang, Zhiwei Fang, Zhaoxiang Liu, Wei Chu, Yuan Zhou, Jianhao Zhang, Rongbo Wu, Min Wang, Tao Lű, Ya Cheng

Bibliographic record

VenueOptics Letters · 2020
Typearticle
Languagelv
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Victoria
FundersFundamental Research Funds for the Central UniversitiesNational Key Research and Development Program of ChinaScience and Technology Commission of Shanghai MunicipalityChinese Academy of SciencesNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMaterials scienceLithium niobateLasing thresholdLaserOptoelectronicsResonatorOpticsWavelengthDopingContinuous waveOptical pumpingLaser pumpingSlope efficiencyFiber laserPhysics

Abstract

fetched live from OpenAlex

We demonstrate a C-band wavelength-tunable microlaser with an E r 3 + -doped high quality ( ∼ 1.8 × 10 6 ) lithium niobate microdisk resonator. With a 976 nm continuous-wave pump laser, lasing action can be observed at a pump power threshold lower than 400 µW at room temperature. Furthermore, the microdisk laser wavelength can be tuned by varying the pump laser power, showing a tuning efficiency of ∼ − 17.03 p m / m W at low pump power below 13 mW, and 10.58 pm/mW at high pump power above 13 mW.

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 score0.004
Threshold uncertainty score0.013

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)0.0040.001

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 head0.014
GPT teacher head0.207
Teacher spread0.193 · 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

Citations127
Published2020
Admission routes2
Has abstractyes

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