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Record W2002451396 · doi:10.1364/oe.18.004740

Mid-IR multiwavelength difference frequency generation based on fiber lasers

2010· article· en· W2002451396 on OpenAlexaff
Jian Jiang, Jianhua Chang, Sujuan Feng, Li Wei, Qinghe Mao

Bibliographic record

VenueOptics Express · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsOpticsMaterials scienceLaserLasing thresholdFiber laserWavelengthBandwidth (computing)Dispersion (optics)OptoelectronicsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

A mid-IR multiwavelength difference frequency generation (DFG) laser source with fiber laser fundamental lights is demonstrated by using the dispersion property of PPLN to broaden the quasi-phase-matching (QPM) acceptance bandwidth (BW). Our results show that the QPM BW for the pump YDFL is much larger than that for the signal EDFL. Using a multiwavelength YDFL and a single-wavelength EDFL as the pump and the signal lights, the DFG laser source can simultaneously emit 14 mid-IR wavelengths with the spacing of 14 nm at a fixed PPLN temperature. Moreover, mid-IR multiwavelength lasing lines can be synchronously tuned between 3.28 and 3.47 microm.

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 score0.089
Threshold uncertainty score0.763

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 head0.014
GPT teacher head0.243
Teacher spread0.229 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

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