Performance of a Hot Rb Vapour-Based Portable Quantum Memory
Bibliographic record
Abstract
Quantum repeaters will be paramount to the success of the future quantum internet. Presently however, the losses incurred in fibre communications are unsustainable when fragile quantum states are transmitted over long distances. The most effective repeater nodes will require incorporation of a minimum of two quantum memory units (QMems) for successful operation. Therefore a network composed of numerous nodes will ideally require scalable repeaters that contain QMems that are portable, robust and do not require a high amount of overhead. Here we investigate the performance of a commercial QMem based on a warm vapour of Rb atoms. Specifically, we characterize the coherence time, absolute efficiency, signal to noise ratio and bit error ratio of this device over a range of vapour temperatures that are readily controllable. For our system, we place these performance metrics into the same conventions as those established for current optical communication protocols. Development of QMem systems meeting these benchmarks will be a vital step for seamless integration of QMems systems into present-day communication architectures.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".