Pump power control of photon statistics in a nanowire quantum dot
Bibliographic record
Abstract
Through fluctuations in the local composition, InAsP quantum dots embedded within site-selected InP nanowires are observed to display biexciton binding energies spanning a range between $\ensuremath{-}0.3\phantom{\rule{0.16em}{0ex}}\mathrm{meV}$ and $+2.9\phantom{\rule{0.16em}{0ex}}\mathrm{meV}$. From this range we select dots having energy-degenerate exciton and biexciton emission and observe an excitation rate-mediated transition from sub- to super-Poissonian second-order correlation statistics. Under pulsed excitation, ${g}^{(2)}(\ensuremath{\tau}=0)$ is found to increase from 0.5 at high excitation levels, rising to 28 as the excitation is reduced by two orders of magnitude. The observed second-order correlation statistics are interpreted using both a stochastic model and a rate equation model of the competition between the various excitonic emission processes. Our results demonstrate that nanowire quantum dots represent a promising approach to the efficient generation of twin-photon states.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".