Portable, broadband, and sensitive terahertz time-domain spectrometer
Bibliographic record
Abstract
Terahertz time-domain spectroscopy (THz-TDS) is a method used in research and industry for non-invasive characterization of products and materials. Many THz-TDS systems rely on parametric conversion in semiconductor crystals to generate and detect phase-locked THz pulses, providing reliable access to frequencies below 3 THz. Accessing higher frequencies, however, often requires a sophisticated near-infrared (NIR) source delivering sub- 100 fs pulses to access the required spectral bandwidth and thin nonlinear crystals (few hundred micrometers thick) to minimize phase mismatch during both the THz generation and detection processes. As a result, broadband THz- TDS configurations rely on laser systems which are often bulky and costly, resulting in inefficient THz generation and detection processes due to a limited nonlinear interaction length in the crystals. To overcome these limitations, we introduce three modules to a THz-TDS system employing a compact and cost-effective pulsed laser. First, a fiberbased component is used to broaden the output laser spectrum and compress the pulse duration. This module provides the NIR frequency content needed for broadband THz generation through optical rectification and a pulse duration short enough to efficiently resolve high THz frequencies during electro-optic sampling. The other two modules utilize a thick nonlinear crystal with a periodically patterned surface to optimize the efficiencies of the broadband THz generation and detection processes. In this configuration, a long nonlinear interaction length is guaranteed while noncollinear phase matching provides access to a broad spectral range. The combination of these modules extends the THz spectrum from 3 THz to beyond 6 THz with a peak dynamic range >50 dB at 3.5 THz.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".