Multisubband plasmons: Beyond the parabolicity in the semiclassical model
Bibliographic record
Abstract
This work studies the impact of the nonparabolicity on the formation of multisubband plasmons. We explore three semiclassical optical response models and compare their predictions to temperature-dependent absorption measurements from three structures: all doped GaAs/AlGaAs quantum wells with continuously varied parabolic binding potentials. We show that qualitative improvement in the prediction of the plasmon absorption peak can only be obtained by including both the energy and wave-function dependence on the in-plane wave vector. Our model, developed to include both these dependencies, uses a $\stackrel{P\vec}{k}\ifmmode\cdot\else\textperiodcentered\fi{}\stackrel{P\vec}{p}$-derived current density operator (instead of the usual scalar effective mass one). The model should be readily generalizable to a wide set of nanostructures, such as asymmetric half-parabolic wells or narrow band materials nanostructures beyond the quasi-Kohn regime.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".