Catadioptric optics for high-resolution terahertz imager
Bibliographic record
Abstract
INO has developed infrared camera systems with microscanning capabilities in order to increase image resolution. It has been shown in previous works that the image quality may be improved even if the pixel pitch is smaller than the point spread function. This paper introduces a catadioptric optics system with fully integrated microscan for improved resolution in the THz band. The design, inspired by the INO's HRXCAM infrared camera core and adapted for terahertz wavelengths, includes two mirrors and one refractive element. It has a 11.9 degree full field of view and an effective F-number of 1.07 over a wide spectral range, from 100 μm to 1.5 mm wavelength. This diffraction limited optics is used to provide video rate high quality THz images. A THz camera, with 160 x 120 pixel and 52 μm pitch detector, is combined with the microscan objective to provide a 320 x 240 pixel image with a 26 μm sampling step. Preliminary imaging results using a THz illumination source at 118 μm wavelength are presented. A comparison between standard and microscanned images is also presented.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".