Polarization-controlled Brillouin scattering in elliptical optophononic resonators
Bibliographic record
Abstract
The fast-growing development of optomechanical applications has motivated advancements in Brillouin scattering research. In particular, the study of high-frequency acoustic phonons at the nanoscale is interesting due to the large range of interactions with other excitations in matter. However, standard Brillouin spectroscopy schemes rely on fixed wavelength filtering, which limits their usefulness for the study of tunable optophononic resonators. It has been recently demonstrated that elliptical optophononic micropillar resonators induce different energy-dependent polarization states for the Brillouin and the elastic Rayleigh scattering and that a polarization filtering setup could be implemented to increase the contrast between the inelastic and elastic scattering of the light. An optimal filtering configuration can be reached when the polarization states of the laser and the Brillouin signal are orthogonal to each other. In this work, we theoretically investigate the parameters of such polarization-based filtering techniques to enhance the efficiency of Brillouin scattering detection. For the filtering optimization, we explore the initial wavelength and polarization state of the incident laser, as well as the ellipticity of the micropillars, and reach an almost optimal configuration for nearly background-free Brillouin detection. Our findings are one step forward in the efficient detection of Brillouin scattering in nanostructures for potential applications in fields such as optomechanics and quantum communication.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".