Quasinormal mode theory and modelling of electron energy loss spectroscopy for plasmonic nanostructures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding light-matter interactions using localized surface plasmons (LSPs) is of fundamental interest in classical and quantum plasmonics and has a wide range of applications. In order to understand the spatial properties of LSPs, electron energy loss spectroscopy (EELS) is a common and powerful method of spatially resolving the extreme localized fields that can be obtained with metal resonators. However, modelling EELS for general shaped resonators presents a major challenge in computational electrodynamics, requiring the full photon Green function as a function of two space points and frequency. Here we present an intuitive and computationally simple method for computing EELS maps of plasmonic resonators using a quasinormal mode (QNM) expansion technique. By separating the contribution of the QNM and the bulk material, we give closed-form analytical formulas for the plasmonic QNM contribution to the EELS maps. We exemplify our technique for a split ring resonator, a gold nanorod, and a nanorod dimer structure. The method is accurate, intuitive, and gives orders of magnitude improvements over direct dipole simulations that numerically solve the full 3D Maxwell equations. We also show how the same QNM Green function can be used to obtain the Purcell factor (and projected local density of optical states) from quantum dipole emitters or two level atoms, and we demonstrate how the spectral features differ in general to the EELS spectrum.
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.
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 it