Ultrafast coherent manipulation of trions in site-controlled nanowire quantum dots
Bibliographic record
Abstract
Physical implementations of large-scale quantum processors based on solid-state platforms benefit from realizations of quantum bits positioned in regular arrays. Self-assembled quantum dots are well established as promising candidates for quantum optics and quantum information processing, but they are randomly positioned. Site-controlled quantum dots, on the other hand, are grown in pre-defined locations but have not yet been sufficiently developed to be used as a platform for quantum information processing. In this paper, we demonstrate all-optical ultrafast complete coherent control of a qubit formed by the single-spin/trion states of a charged site-controlled nanowire quantum dot. Our results show that site-controlled quantum dots in nanowires are promising hosts of charged-exciton qubits and that these qubits can be cleanly manipulated in the same fashion as has been demonstrated in randomly positioned quantum dot samples. Our findings suggest that many of the related excitonic qubit experiments that have been performed over the past 15 years may work well in the more scalable, site-controlled systems, making them very promising for the realization of quantum hardware.
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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".