Bright entangled photon pair generation from a quantum dot in a weak nanowire cavity
Bibliographic record
Abstract
A quantum dot (QD) embedded on-axis in a tapered photonic nanowire waveguide on a gold mirror is a promising platform for generating on-demand entangled photon pairs. Site-selected InP nanowires can be grown with high-quality InAsP QDs emitting from 870 nm to 1550 nm. However, the nanowire quantum dots (NWQDs) cannot be grown directly on gold, and therefore the photon pair extraction efficiency was measured to be ~6% on the substrate since the QD emits in both directions of the waveguide. We developed a pick-and-place transfer technique, to deterministically move NWQDs onto a gold mirror without degradation of the optical characteristics of the QD. We observe a 2.5-fold enhancement in brightness and a 1.58x decrease in the lifetime due to a weak Purcell enhancement. This corresponds to an increase of the pair extraction efficiency to ~49% on gold. Combining this with a previous result showing near-unity entanglement fidelity from the same NWQD platform, we aim to overcome the fundamental limit of probabilistic entangled photon pair sources to develop a truly deterministic entangled photon pair source.
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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 | 0.001 |
| 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".