Superlens coupling to object and image: A secondary resonance mechanism to improve single-negative imaging of electromagnetic waves
Bibliographic record
Abstract
Superlens slabs rely on the coherent superposition of multiply reflected evanescent waves to amplify and restore the fine details of an object at the image plane. If a superlens slab is placed in close proximity to a source object and image detector, similar interactions with these external components can introduce resonances outside of the superlens. In this work, we explore the role of external resonances on single-negative slab superlens performance by considering a complete electromagnetic imaging system containing a physical source object and image detector, each modeled as a planar dielectric half-space. In studying the transmission of spectral components that carry real power through this system, we find that resonances outside the lens can have a dramatic impact on single-negative superlens performance. In particular, we find that the resonances external to a μ-negative lens can be used to extend the imaging range beyond the extreme near field and maintain super-resolution even in the presence of loss.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".