Zeptojoule detection of terahertz pulses by parametric frequency upconversion
Bibliographic record
Abstract
We combine parametric frequency upconversion with the single-photon counting technology to achieve terahertz (THz) detection sensitivity down to the zeptojoule (zJ) pulse energy level. Our detection scheme employs a near-infrared ultrafast source, a GaP nonlinear crystal, optical filters, and a single-photon avalanche diode. This configuration is able to resolve 1.4 zJ (1.4 × 10 –21 J) THz pulse energy, corresponding to 1.5 photons per pulse, when the signal is averaged within only 1 s (or 50,000 pulses). A single THz pulse can also be detected when its energy is above 1185 zJ. These numbers correspond to the noise-equivalent power and THz-to-NIR photon detection efficiency of 1.3 × 10 –16 W/Hz 1/2 and 5.8 × 10 –2 %, respectively. To test our scheme, we perform spectroscopy of the water vapor between 1 and 3.7 THz and obtain results that are in agreement with those acquired with a standard electro-optic sampling (EOS) method. Our technique provides a 0.2 THz spectral resolution offering a fast alternative to EOS THz detection for monitoring specific spectral components in spectroscopy, imaging, and communication applications.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".