Spatial and spectral characteristics in realizations of broadband terahertz spectroscopy on a subwavelength scale
Bibliographic record
Abstract
Abstract In this work, we take aim at the fundamental challenge for realizations of broadband terahertz (THz) spectroscopy on a subwavelength scale. We introduce apertured THz microjets in this effort to resolve the fundamental limits of spatial resolution and spectral bandwidth. The THz microjets are formed as intense foci at the rear of engineered (microcomposite) spheres and are coupled through subwavelength (circular) apertures. Such coupling enables effective transmission of THz power through samples with broad spectral bandwidths and fine spatial resolutions. We show that the apertures function as high-pass filters, with their diameter d enabling strong transmission above a cutoff frequency fc. Our theoretical and experimental results reveal that the values for d and fc are prescribed by a fixed spatial-spectral product dfc, whereby reductions in d (to improve the spatial resolution) can raise fc into the targeted spectrum (at the expense of spectral bandwidth). We use this understanding to demonstrate broadband (0.3–0.7 THz) THz spectroscopy of lactose at the subwavelength (365 µm) scale. These results for apertured THz microjets represent a 20-fold improvement in spatial resolution over analogous apertured THz plane waves. Overall, our findings show promise for studies of carcinogenesis, pathogenesis, and the like.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".