Terahertz time-domain spectroscopy of single-atom defects
Bibliographic record
Abstract
As device features approach the atomic limit, next generation experimental techniques must characterize them on both their intrinsic length and time scales. The THz range of the electromagnetic spectrum hosts material excitations that are critical for nanotechnology, including the collective motion of charges, ions, and spins. These excitations are often studied with far-field terahertz time-domain spectroscopy, which directly measures the oscillating electric field of a terahertz pulse and relates it to key material processes through the light-matter interaction. Here we show how lightwave-driven microscopy can be used as a platform for atomic-scale terahertz time-domain spectroscopy. As a demonstration, we first apply our new technique to silicon-vacancy centers at the surface of GaAs and discover a single-atom resonator with features reminiscent of the technologically important DX center. Next, we investigate van der Waals materials with atomic-scale terahertz time-domain spectroscopy and demonstrate how atomic defects may be distinguished from the pristine surface by their characteristic vibrational fingerprint.
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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".