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Record W3158594218 · doi:10.1364/oe.421008

Tapered transmission lines for terahertz systems

2021· article· en· W3158594218 on OpenAlexafffund
Levi Smith, Walid Gomma, Hadi Esmaeilsabzali, Thomas E. Darcie

Bibliographic record

VenueOptics Express · 2021
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsSimon Fraser UniversityUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTerahertz radiationOpticsTransmission lineAttenuationTransmission (telecommunications)Electric power transmissionCharacteristic impedanceMaterials scienceLine (geometry)Pulse shapingPhysicsTelecommunicationsComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

Complex terahertz (THz) System-on-Chip (TSoC) circuits require ultra-wideband low-loss low-dispersion interconnections between building-block components of various dimensions and characteristics. Tapered transmission lines, which enable the gradual transformation of both physical dimensions and characteristic impedance, are a convenient basis for these interconnections. In this paper, we quantify both experimentally and through simulation, the efficacy of transmission-line tapers connecting two different coplanar-strip transmission-line configurations, for frequencies up to 2.0 THz and with 25 GHz spectral resolution. We demonstrate tapers that enable transitioning from a small device-constrained transmission-line dimension (10 μm line width) to a lower-loss (20-40 μm line width) dimension, as a method to reduce the overall attenuation, and outline design constraints for tapered sections that have minimal detrimental impact on THz pulse propagation.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.334

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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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

Citations12
Published2021
Admission routes2
Has abstractyes

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