MétaCan
Menu
Back to cohort

Noncollinear parametric detection of broadband terahertz pulses

2023· article· en· W4388075893 on OpenAlexaff
S. Mine, G. Gandubert, L. Guiramand, X. Ropagnol, Kosuke Murate, F. Blanchard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsTerahertz radiationBroadbandParametric statisticsOptical parametric amplifierOptoelectronicsMaterials scienceOpticsPhysicsOptical amplifierLaser

Abstract

fetched live from OpenAlex

We present a new method for broadband terahertz (THz) pulse detection by parametric process in a non-collinear phase matching geometry using a lithium niobate (LN) crystal. Counterintuitively, our results show the ability to spatially separate the broadband up-converted signal with a resolution of a few GHz. This striking result will have a significant impact for advanced sensing of THz light detection, whether for single-shot spectroscopy or for ultrafast information transmission in this frequency range.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicTerahertz technology and applicationsFrench-language works237,207