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Record W2952666811 · doi:10.1109/iwat.2019.8730646

Reconfigurable Terahertz Array Antenna

2019· article· en· W2952666811 on OpenAlexaff
Kathirvel Nallappan, Hichem Guerboukha, Maksim Skorobogatiy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTerahertz radiationReconfigurable antennaAntenna (radio)Computer scienceAntenna arrayDipole antennaOptoelectronicsElectronic engineeringPhysicsTelecommunicationsCoaxial antennaEngineering

Abstract

fetched live from OpenAlex

Terahertz imaging with high speed acquisition and spatial resolution is desired in many practical applications. In this work, a proof of concept for high speed near-field imaging with sub-wavelength resolution using spatial light modulator is presented. An 8 channel THz detector array antenna with an electrode gap of 100 μm and length of 5 mm is fabricated using the commercially available GaAs semiconductor substrate. Each array antenna can be excited simultaneously by spatially reconfiguring the optical probe beam. The detected spatial THz electric field can be recorded using 8 channel lock-in amplifiers. By scanning the probe beam along the length of the array antenna, a 2D image can be obtained with amplitude, phase and frequency information. The time taken to reconstruct the image is limited only by the speed of the delay line to record the THz pulse at each spatial location.

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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.182
Teacher spread0.178 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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