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Subcycle Terahertz Nonlinear Optics

2018· article· en· W2895566559 on OpenAlexafffund
X. Chai, X. Ropagnol, S. Mohsen Raeis-Zadeh, M. Reid, Safieddin Safavi‐Naeini, T. Ozaki

Bibliographic record

VenuePhysical Review Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of Northern British ColumbiaÉcole de Technologie SupérieureUniversity of WaterlooInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de l'Enseignement Supérieur, de la Recherche, de la Science et de la Technologie
KeywordsTerahertz radiationPhysicsOpticsTerahertz gapTerahertz spectroscopy and technologyUltrashort pulsePhotomixingHarmonicsNonlinear opticsOptical rectificationElectromagnetic pulseOptoelectronicsFar-infrared laserLaserVoltageQuantum mechanics

Abstract

fetched live from OpenAlex

The nonlinear interaction of subcycle electromagnetic radiation with matter is the current frontier in ultrafast nonlinear optics and high-field physics. Here, we investigate nonlinear optical effects induced by intense, subcycle terahertz radiation in a doped semiconductor. We observe a truncation of the half-cycle terahertz pulse and an emission of high-frequency terahertz photons. We attribute our observations to the abrupt current drop caused by strong intervalley scattering effects. By adding an extra half-cycle terahertz pulse with opposite polarity, we monitor the evolution of the nonlinear carrier dynamics during a quasi-single-cycle pulse. Our results demonstrate the differences between nonlinear effects for subcycle and multicycle terahertz pulses. It also suggests a new approach to subcycle control of terahertz waveforms, and the generation of high-order terahertz harmonics could be realized by using multicycle pulses.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.010
GPT teacher head0.267
Teacher spread0.257 · 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

Citations70
Published2018
Admission routes2
Has abstractyes

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