Towards deterministic quantum photonic information processing with quantum dot phase shifters
Bibliographic record
Abstract
Semiconductor quantum dots (QDs) are a type of solid-state quantum emitter that can act as a near-ideal quantum light-matter interface when integrated with high-quality nanophotonic systems. Though QDs have typically been used to create state-of-the-art, on-demand single photon sources, here we widen the perspective on QDs, showing how to design quantum photonic integrated circuits based on both linear and nonlinear QD phase shifters. Specifically, we find that linear QD phase shifters can be used to realize cryogenically-compatible, fast, low-loss, and high-fidelity reconfigurable linear circuits. When paired with QDs that mediate interactions between photonic qubits, generating nonlinear phase shifts, deterministic quantum photonic logic gates can be achieved. Thus, our work paves the way for the realization of on-chip, cryogenically-compatible linear and nonlinear quantum photonic circuits, including quantum photonic neural networks, which can form the foundation for scalable and efficient quantum photonic technologies.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".