Ultraslow waves on the nanoscale
Bibliographic record
Abstract
There has recently been a surge of interest in the physics and applications of broadband ultraslow waves in nanoscale structures operating below the diffraction limit. They range from light waves or surface plasmons in nanoplasmonic devices to sound waves in acoustic-metamaterial waveguides, as well as fermions and phonon polaritons in graphene and van der Waals crystals and heterostructures. We review the underlying physics of these structures, which upend traditional wave-slowing approaches based on resonances or on periodic configurations above the diffraction limit. Light can now be tightly focused on the nanoscale at intensities up to ~1000 times larger than the output of incumbent near-field scanning optical microscopes, while exhibiting greatly boosted density of states and strong wave-matter interactions. We elucidate the general methodology by which broadband and, simultaneously, large wave decelerations, well below the diffraction limit, can be obtained in the above interdisciplinary fields. We also highlight a range of applications for renewable energy, biosensing, quantum optics, high-density magnetic data storage, and nanoscale chemical mapping.
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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) | 0.001 | 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".