Technologies for focusing and aperturing terahertz radiation in the realization of terahertz spectroscopy on the subwavelength scale
Bibliographic record
Abstract
This work demonstrates the realization of terahertz (THz) spectroscopy on a subwavelength scale. We do so by using dielectric spheres as focusing elements and apertures as spatially constricting elements for THz radiation. Such a configuration forms intense, subwavelength-sized THz microjets. Two implementations are used to demonstrate the effectiveness of THz microjets, as follows: apertured THz plane waves and apertured THz microjets. Seven aperture diameters were chosen for each implementation to discern their capabilities at the subwavelength scale. We investigated the effectiveness of each implementation in mapping the material characteristics of the sample onto the THz beam. Such analyses show that apertured THz microjets were able to map material characteristics (via refractive index and extinction coefficient) onto the beam (via phase and amplitude) effectively and reliably. This is expected as the beam produced by apertured THz microjets has a small cross-sectional area (apertures) and high intensity (THz microjets). Here, we illustrate the capabilities of apertured THz microjets for a biological specimen, being lactose, to show the potential for biological applications. Overall, this work demonstrates the ability of apertured THz microjets to perform THz spectroscopy at a subwavelength scale. Such findings could bring about biological characterization with cellular-scale resolution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".