Emission and sensing of high-frequency terahertz electric fields using a GaSe crystal
Bibliographic record
Abstract
A GaSe crystal cut along the (001) crystallographic plane is investigated for the emission and detection of high-frequency (i.e. up to ∼20 THz) electric fields. To date, a comprehensive analysis on high-frequency difference frequency generation and electro-optic sensing in GaSe has not been performed and should consider aspects such as electric field polarization orientation, symmetries inherent to the crystal structure, and the various possible generation and detection phase-matching arrangements. Herein, terahertz radiation generation is investigated for various excitation electric field polarizations as the GaSe crystal is rotated in the (001) plane. Subsequently, the crystal is rotated out-of-plane to investigate the difference frequency generation and electro-optic sampling phase-matching conditions for various arrangements. The measured terahertz radiation spectra show peak generation at the frequencies of 10, 16, and 18 THz (dependent on the GaSe crystal orientation), in agreement with the frequencies exhibiting perfect phase-matching. GaSe has the potential to emerge as the primary crystal for the emission and detection of high-frequency electric fields, such that this comprehensive analysis is necessary for the widespread adoption and practical implementation of GaSe as a high-frequency source crystal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".