Method for high resolution and wideband spectroscopy in the terahertz and far-infrared region
Bibliographic record
Abstract
Asynchronous electro-optic sampling (A-EOS) using two mode-locked lasers with slightly different pulse repetition rates has significantly advanced high-speed time-domain terahertz (THz) spectroscopy on several practical fronts. However, A-EOS also holds strong potential as a precision frequency measurement technique. By carefully considering A-EOS in the frequency domain as a pair of femtosecond frequency combs with a detuned comb spacing, we show there exists a unique one-to-one mapping between a THz frequency comb and the resulting radio frequency comb of the A-EOS signal. With reasonable frequency comb spacing (0.1 to 1 GHz) and detuning frequencies (1 to 50 kHz) of the combs’ repetition rates, interrogation bandwidths of >10 THz centered between 10 to 100 THz (300 to 3000 cm−1) are possible. Furthermore, we calculate the effect of nonuniform spectral phase of the sampling pulse train and wave-vector mismatch within a ZnTe sampling crystal on the expected heterodyne beat signal.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".