Probing Spectral-Hole-Burning in Non-Hermitian Scatterings: Differentiating Far-Field Interference and Near-Field Coupling
Bibliographic record
Abstract
Scattering spectra from radiative non-Hermitian systems often exhibit intricate line shapes, where peaks typically garner the most attention for mode identification. However, in multimode systems, the valleys between these peaks may contain valuable information. This “coupling” feature arises from the nonorthogonality of modes in both far and near fields, giving rise to diverse and complex spectra-hole-burning (SHB) patterns. Traditionally, the interpretation of these SHBs has focused on Rabi splitting or Fano resonances, often concentrating solely on either far-field interference or near-field coupling. However, it is essential to recognize that both phenomena coexist in non-Hermitian scatterings. In this study, we develop a quantitative quantum model to probe scattering SHB by simultaneously extracting near-field coupling rates between system quasinormal modes, nonradiative decay rates into a heat reservoir, and radiative decay rates into a vacuum reservoir for far-field interference. We apply our model to illustrate the concept of geometric engineering in tuning the ratio of far-field interference and near-field coupling, exemplified by a silver dimer transitioning from cube-dimer to sphere-dimer or cube-dimer to nanocube-on-mirror configurations. Through this, we establish a universal design guideline for non-Hermitian scattering by creating a two-mode SHB library based on arbitrarily tunable far-field interference and near-field coupling. The developed model serves as a generalized diagnostic tool for probing the SHB mechanisms in all types of non-Hermitian scattering problems, promising to advance our understanding of intricate phenomena and facilitate the design of tailored optical devices with enhanced performance and functionality.
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 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".