Invited Article: Ultra-broadband terahertz coherent detection via a silicon nitride-based deep sub-wavelength metallic slit
Bibliographic record
Abstract
We present a novel class of CMOS-compatible devices aimed to perform the solid-state-biased coherent detection of ultrashort terahertz pulses, i.e., featuring a gap-free bandwidth at least two decades-wide. Such a structure relies on a 1-µm-wide slit aperture located between two parallel aluminum pads, embedded in a 1-µm-thick layer of silicon nitride, and deposited on a quartz substrate. We show that this device can detect ultra-broadband terahertz pulses by employing unprecedented low optical probe energies of only a few tens of nanojoules. This is due to the more than one order of magnitude higher nonlinear coefficient of silicon nitride with respect to silica, the nonlinear material employed in the previous generations. In addition, due to the reduced distance between the aluminum pads, very high static electric fields can be generated within the slit by applying extremely low external bias voltages (in the order of few tens of volts), which strongly enhance the dynamic range of the detected THz waveforms. These results pave the way to the integration of solid-state ultra-broadband detection in compact and miniaturized terahertz systems fed by high repetition-rate laser oscillators and low-noise, low-voltage generators.
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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 | 0.000 |
| 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 | 0.000 |
| 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 | 0.001 |
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".