Destruction and enhancement of photonic band gap and coherent localization of optical fields in functional photonic crystals
Bibliographic record
Abstract
We use electromagnetically induced transparency combined with coherent enhancement of refractive index in the conduction intersubband transitions of a n-doped quantum well structure to study one-dimensional functional (active) photonic band gap structures. In the absence of a control laser field, such structures act as conventional photonic band gaps created by off-resonant (background) refractive index perturbations. In the presence of the control field, they are transformed into resonant structures with transitions around the Bragg wavelength. We show that this process can be used to (i) destroy the band gap, making the structure fully transparent around the Bragg wavelength, or (ii) coherently tune the band gap while enhancing its width by nearly a factor of 2. Using these phenomena we then study coherent localization of electromagnetic modes in photonic band gap structures without having any structural defects. Such a localization process here happens via partial illumination of such structures by the control field, generating electromagnetically induced optical defects. We show that the phase associated with such defects can be adjusted by the control field, allowing us to generate tunable electromagnetically induced transmission resonances (or photonic electromagnetically induced transparency) within the band gap.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".