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Polygon Coherent Modes in a Weakly Perturbed Whispering Gallery Microresonator for Efficient Second Harmonic, Optomechanical, and Frequency Comb Generations

2020· article· en· W3027971789 on OpenAlexafffund
Zhiwei Fang, Sanaul Haque, Saeed Farajollahi, Haipeng Luo, Jintian Lin, Rongbo Wu, Jianhao Zhang, Zhe Wang, Min Wang, Ya Cheng, Tao Lű

Bibliographic record

VenuePhysical Review Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Victoria
FundersScience and Technology Commission of Shanghai MunicipalityNational Key Research and Development Program of ChinaDefense Threat Reduction AgencyChinese Academy of SciencesNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsWhispering-gallery waveOpticsPhysicsPolygon (computer graphics)OptoelectronicsResonatorTelecommunications

Abstract

fetched live from OpenAlex

We observe high optical quality factor (Q) polygonal and star coherent optical modes in a lithium niobate microdisk. In contrast to the previous polygon modes achieved by deformed microcavities at lower mechanical and optical Q, we adopt weak perturbation from a tapered fiber for the polygon mode formation. The resulting high intracavity optical power of the polygon modes triggers second harmonic generation at high efficiency. With the combined advantages of a high mechanical Q cavity, we observe optomechanical oscillation in polygon modes for the first time. Finally, we observe frequency microcomb generation from the polygon modes with an ultrastable taper-on-disk coupling mechanism.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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 designSimulation or modeling
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

Citations38
Published2020
Admission routes2
Has abstractyes

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