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Record W3206091767 · doi:10.1364/ol.442281

Electrically pumped widely tunable O-band hybrid lithium niobite/III-V laser

2021· article· en· W3206091767 on OpenAlexaff
Ya Han, Xian Zhang, Fujin Huang, Xiaoyue Liu, Mengyue Xu, Zhongjin Lin, Mingbo He, Siyuan Yu, Ruijun Wang, Xinlun Cai

Bibliographic record

VenueOptics Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of British Columbia
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsLithium niobateMaterials scienceOptoelectronicsLaserPhotonic integrated circuitOpticsLasing thresholdResonatorPhotonicsWavelengthPhysics

Abstract

fetched live from OpenAlex

Significant improvements in the lithium niobate on insulator (LNOI) platform are pushing LNOI-based laser sources to the forefront of integrated photonics. Here, we report the first, to the best of our knowledge, electrically pumped hybrid lithium niobate/III-V laser by butt coupling an InP-based optical gain chip with a LNOI photonic integrated circuit (PIC). In the PIC, a Vernier filter consisting of two LNOI microring resonators is employed to select the lasing wavelength. A wavelength tuning range of more than 36 nm is achieved in the O band. The hybrid laser has a maximum on-chip optical power of 2.5 mW and threshold current density of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mn>2.5</mml:mn> <mml:mspace width="thickmathspace"/> <mml:msup> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">k</mml:mi> <mml:mi mathvariant="normal">A</mml:mi> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo>/</mml:mo> </mml:mrow> <mml:mi mathvariant="normal">c</mml:mi> <mml:mi mathvariant="normal">m</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:math> . A side mode suppression ratio better than 60 dB is achieved.

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 score0.073
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.187
Teacher spread0.182 · 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

Citations65
Published2021
Admission routes1
Has abstractyes

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