Widely tunable solid-state source of single-photons matching an atomic transition
Bibliographic record
Abstract
Abstract Hybrid quantum technologies aim to combine diverse quantum systems, mirroring classical computers' integration of electronic, photonic, magnetic, and mechanical components. Quantum dots in semiconductor nanowires emit high-purity, deterministic single photons with high repetition, while atomic ensembles offer photon storage and strong optical nonlinearities controllable by single photons. To interface quantum dots with atomic ensembles successfully, precise optical frequency matching of these two platforms is crucial. We demonstrate a simple, precise, reversible, broad-range, and local method for controlling the emission frequency of individual quantum dots embedded in tapered semiconductor nanowires. We then interface the quantum dots with an atomic ensemble via single-photons matched to hyperfine transitions and slow-light regions of the cesium D1-line. Our approach allows linking atomic and solid-state quantum systems and can potentially also be applied to other types of nanowire-embedded solid-state emitters, as well as for creating devices based on multiple solid-state emitters tuned to produce indistinguishable photons.
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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 | 0.000 |
| 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) | 0.001 | 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".