Bibliographic record
Abstract
We report on the nonlinear spectroscopy of crystalline quartz in the terahertz (THz) region. We observe that with increasing of the THz peak amplitude, the pulse experiences a larger delay in travelling through the sample. We estimate a nonlinear refractive index of the order of $10^{-13} \mathrm{~m}^{2} / \mathrm{W}$, which is several orders of magnitude larger than the typical values for nonlinear refractive indices of solids in the visible region. Furthermore, a negative fifth-order susceptibility of the order of $10^{-30} \mathrm{~m}^{4} / \mathrm{V}^{4}$ is measured. In the second part, we present a simple method to model the propagation of a broadband THz pulse in a nonlinear medium with nonlinear refractive index dispersion using a spectral solution to the wave equation based on Fourier analysis. This method is a useful tool to investigate the effects of the nonlinear dispersion on the propagation of ultrashort THz pulses in a straightforward fashion. Furthermore, based on the same model, we derive an expression to extract the nonlinear refractive index dispersion for broadband sources and compare it with the approximate methods previously proposed: monochromatic approximation and sharp-resonance approximation. We perform a simulation on a sample with an arbitrary dispersion for nonlinear refractive index, and successfully extract the dispersion from the simulated propagation output.
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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 | 0.000 |
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".