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Record W1968460988 · doi:10.1109/tthz.2015.2412381

Frequency Tunable Continuous THz Wave Generation in a Periodically Poled Fiber

2015· article· en· W1968460988 on OpenAlexaff
Weilin Liu, Jiejun Zhang, Maxime Rioux, Jeff Viens, Younès Messaddeq, Jianping Yao

Bibliographic record

VenueIEEE Transactions on Terahertz Science and Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsTerahertz radiationMaterials scienceOpticsOptoelectronicsOptical fiberPhysics

Abstract

fetched live from OpenAlex

An all-fiber approach to terahertz generation using a periodically poled optical fiber is proposed and experimentally demonstrated. In the proposed approach, a continuous-wave THz wave is generated at a periodically poled fiber by beating two optical wavelengths from two laser sources with the wavelength spacing corresponding to the frequency of the THz wave. The key component in the system is the periodically poled fiber, which is made by a twin-hole fiber with the fiber core residing between two holes. The twin-hole fiber is then thermally poled at a temperature of ~ 260°C with a voltage of 3.3 kV applied to the silver electrodes inside the two holes to introduce second-order nonlinearity. The quasi phase matching (QPM) condition is achieved by periodically erasing the thermal poling induced second-order nonlinearity with an ultraviolet laser, which enhances the energy conversion efficiency. The proposed approach is validated by an experiment. The emission of a THz wave centered at 3.8 THz with an output power of 0.5 μW is observed. The frequency tunability between 2.2 and 3.8 THz is also experimentally demonstrated.

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 score0.000
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 head0.016
GPT teacher head0.221
Teacher spread0.204 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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