Microcavity effects in ensembles of silicon quantum dots coupled to high‐<i>Q</i> resonators
Bibliographic record
Abstract
Abstract Microcavities can be used to control the spectral properties of ensembles of quantum dots. In this work, spherical microcavities with quality ( Q ) factors as high as 3 × 10 8 in air were coated with a layer of fluorescent silicon quantum dots. After coating, the transmission Q factors decreased to approximately 10 6 or slightly lower, while the luminescence Q ‐factors ( Q PL ) reached a maximum of ∼4000. While these are the highest Q PL values yet reported for Si QDs, Q PL was always orders of magnitude lower than the intrinsic cavity Q . One reason for the difference has its origin in the quantum dot emission linewidth, which is associated only with the Q PL and not with the cold cavity (intrinsic) Q . Essentially, the Q factor in luminescence experiments arises from the spontaneous emission rate enhancements or suppressions experienced by the dot in the cavity. We developed a general model to calculate the luminescence spectrum and decay dynamics for an inhomogeneously broadened ensemble of quantum dots with arbitrary emission linewidths weakly coupled to an optical cavity. Using this model and comparing it with experiment, we show that the respective values of the luminescence quality factors and the cold cavity quality factors can be used to determine an effective quantum dot emission linewidth without the need for single particle spectroscopy. In the case of Si quantum dots, the room temperature emission linewidth may be as small as a few meV at room temperature.
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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 | 0.000 | 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 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".