Ultrahigh Purcell factors and Lamb shifts in slow-light metamaterial waveguides
Bibliographic record
Abstract
We introduce the complex band structure and a medium-dependent (Green's function) quantum-optics formalism to study the enhanced spontaneous emission factors and Lamb shifts from a quantum dot or atom near the surface of a slow-light metamaterial waveguide. Using a realistic loss factor of $\ensuremath{\gamma}/2\ensuremath{\pi}=2\text{ }\text{THz}$, Purcell factors of approximately 250 and 100 are found at optical frequencies for $p$-polarized and $s$-polarized dipoles, respectively, placed 28 nm $(0.02{\ensuremath{\lambda}}_{0})$ above the slab surface. For smaller loss values, we demonstrate that the slow-light regime of odd metamaterial waveguide propagation modes can be observed and related to distinct resonances in the Purcell factors. Correspondingly, we predict unusually large and rich Lamb shifts of approximately $\ensuremath{-}1$ to $\ensuremath{-}6\text{ }\text{GHz}$ for a dipole moment of 50 Debye. We also make a direct calculation of the far-field-emission spectra which contains direct measurable access to these enhanced Purcell factors and Lamb shifts.
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 | 0.000 |
| 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".