Pulsed excitation dynamics in quantum-dot–cavity systems: Limits to optimizing the fidelity of on-demand single-photon sources
Bibliographic record
Abstract
A quantum dot coupled to an optical cavity has recently proven to be an excellent source of on-demand single photons. Typically, applications require simultaneous high efficiency of the source and quantum indistinguishability of the extracted photons. While much progress has been made in both suppressing background sources of decoherence and utilizing cavity quantum electrodynamics to overcome fundamental limitations set by the intrinsic exciton-phonon scattering inherent in the solid-state platform, the role of the excitation pulse has been often neglected. We investigate quantitatively the factors associated with pulsed excitation that can limit simultaneous efficiency and indistinguishability, including excitation of multiple excitons, multiphotons, and pump-induced dephasing, and find for realistic single-photon sources that these effects cause degradation of the source figures of merit comparable to that of phonon scattering. We also develop rigorous open quantum system polaron master equation models of quantum dot dynamics under a time-dependent drive which incorporate non-Markovian effects of both photon and phonon reservoirs, and explicitly show how coupling to a high-Q-factor cavity suppresses multiphoton emission in a way not predicted by commonly employed models. We then use our findings to summarize the criteria that can be used for single-photon-source optimization.
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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 | 0.003 |
| 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 | 0.002 |
| 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".