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Record W3175018491 · doi:10.1364/oe.428106

Terahertz time-domain derivative spectrometer using a large-aperture piezoelectric micromachined device

2021· article· en· W3175018491 on OpenAlexafffund
F. Amirkhan, Mathieu Gratuze, X. Ropagnol, T. Ozaki, Frédéric Nabki, F. Blanchard

Bibliographic record

VenueOptics Express · 2021
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsInstitut National de la Recherche ScientifiqueÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsTerahertz radiationOpticsSpectrometerModulation (music)SIGNAL (programming language)Time domainAperture (computer memory)PhysicsMaterials scienceOptoelectronicsComputer scienceAcoustics

Abstract

fetched live from OpenAlex

The engineering of optomechanical systems has exploded over the past decades, with many geometries and applications arising from the coupling of light with mechanical motion. The modulation of electromagnetic radiation in the terahertz (THz) frequency range through optomechanical systems is no exception to this research effort. However, some fundamental modulation capabilities for THz communications and/or high-speed data processing applications are yet to be established. Here, we demonstrate a THz time-domain derivative spectrometer based on a piezoelectric micromachined (PM) device. Insertion of the PM device into the THz beam path provides reference modulation for the lock-in detection unit, which in turn provides access to the nth-order derivative information of the incoming THz signal. Strikingly, the integration of the recorded derived signal leads to a recovered reference signal with an equivalent or even better signal-to-noise ratio, opening the door to a new type of highly sensitive THz measurements in the time domain.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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
Published2021
Admission routes2
Has abstractyes

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