Efficient optical pumping and high optical depth in a hollow-core photonic-crystal fibre for a broadband quantum memory
Bibliographic record
Abstract
The generation of large multiphoton quantum states—for applications in computing, metrology and simulation—requires a network of high-efficiency quantum memories capable of storing broadband pulses. Integrating these memories into a fibre offers a number of advantages towards realizing this goal: strong light–matter coupling at low powers, simplified alignment and compatibility with existing photonic architectures. Here, we introduce a large-core kagome-structured hollow-core fibre as a suitable platform for an integrated fibre-based quantum memory with a warm atomic vapour. We demonstrate, for the first time, efficient optical pumping in such a system, where 90 ± 1% of atoms are prepared in the ground state. We measure high optical depths (3 × 10 4 ) and narrow homogeneous linewidths (6 ± 2 MHz) that do not exhibit significant transit-time broadening, showing that we can prepare a Λ-level system in a pure state. Our results establish that kagome fibres are suitable for implementing a broadband, room-temperature quantum memory, as well as a range of nonlinear optical effects.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".