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Record W4392638305 · doi:10.1117/12.3002915

Governing limits of spatial resolution and spectral bandwidth for implementations of terahertz spectroscopy on the subwavelength scale

2024· article· en· W4392638305 on OpenAlexaff
Alexis N. Guidi, Michael E. Mitchell, Jonathan F. Holzman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTerahertz radiationImage resolutionOpticsBandwidth (computing)PhysicsSpectroscopySpectral resolutionSpatial frequencyAperture (computer memory)Computer scienceSpectral lineTelecommunicationsAcoustics

Abstract

fetched live from OpenAlex

In this work, we consider the governing limits of spatial resolution and spectral bandwidth in pursuing implementations of terahertz (THz) spectroscopy on the subwavelength scale. We discuss the need for effective focusing elements in driving sufficient levels of power from the (macroscopic) incident THz beam down to the (microscopic) focal spot. Such elements, when effective, enable large signal strengths and wide bandwidths, but this has proven to be challenging in contemporary implementations of near-field THz imaging and spectroscopy. To this end, we show theoretical and experimental results for focusing via parabolic mirrors, high-resolution lenses, and engineered dielectric spheres, with the latter yielding THz microjets with especially intense and small focal spots. We then discuss the need for near-field spatial constriction, to drive the spatial resolution down to an even smaller scale, and show that this constriction can lead to dispersive (i.e., frequency-dependent) characteristics. In this work, we demonstrate spatial constriction via simple circular apertures, which function as high-pass filters. Ultimately, our theoretical and experimental results reveal that implementations of THz spectroscopy on the subwavelength scale are governed by a spatial-spectral product—whereby reductions in the aperture's diameter (to improve the spatial resolution) raise the aperture's cutoff frequency (at the expense of spectral bandwidth).

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0010.002
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 head0.013
GPT teacher head0.261
Teacher spread0.247 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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