Plasmonic effect on quantum coherence and interference in metallic photonic crystals doped with quantum dots
Bibliographic record
Abstract
We have studied the effect of plasma energy on the absorption coefficient of metallic photonic crystals doped with an ensemble of three-level quantum dots, which are interacting with each other via dipole-dipole interaction. The quantum dots are also interacting with coupled plasma-photon modes present in the system. A probe laser field is applied in order to study the absorption coefficient. We also consider the effect of quantum interference in our simulations, whereby two absorbed photons interfere with one another. Here the density matrix method has been used to calculate the steady-state and transient behavior of the absorption coefficient for the system. Two different field configurations are considered in our numerical simulations. In the first configuration, a probe field couples the ground state and two closely excited states. Absorption occurs due to transitions from the ground state to the two excited states. It is found that the position of the transparent peak moves when the plasma energy is changed. In other words, changing the plasma energy causes the system to switch between a transparent and an absorbing state. The strong coupling between plasmons and the quantum dots is responsible for this phenomenon. In the second configuration, the probe field couples with only one excited state, while a pump field couples to the other excited state. The transition between excited states is dipole forbidden. We observed that the peak in the absorption profile splits into two and also that the system exhibits gain with inversion due to the change in the plasma frequency, which is caused by quantum interference and coherence. These are interesting results and can be used make nanoscale plasma devices.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".