Terahertz solid immersion microscopy: Recent achievements and challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Unique effects of terahertz (THz)-wave–matter interaction push rapid progress in THz optoelectronics aimed at bridging the problematic THz gap. However, majority of modern methods of THz spectroscopy and imaging are still hampered by low spatial resolution. Common lens/mirror-based THz optics fails to overcome the Abbe barrier and usually provides resolution larger than a free-space wavelength λ (i.e., hundreds of micrometers or even few millimeters). To mitigate this difficulty, supperresolution THz imaging modalities were introduced recently, among which we particularly underline different methods of THz scanning-probe near-field microscopy. They not only rely on strong light confinement on sub-wavelength probes and provide resolution down to ∼10−1–10−3λ but also suffer from small energy efficiency or presume an interplay among imaging resolution, signal-to-noise ratio, and performance. In this paper, we consider reflection-mode THz solid immersion (SI) microscopy that offers some compromise between the high imaging resolution of 0.15λ and high energy efficiency, which is due to the absence of any subwavelength probe in an optical scheme. Recent achievements, challenging problems, and prospects of SI microscopy are overviewed with an emphasis on resolving the inverse problem and applications in THz biophotonics.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it