Photon-Interfaced Ten-Qubit Register of Trapped Ions
Bibliographic record
Abstract
Establishing networks of quantum processors offers a path to scalable quantum computing and applications in communication and sensing. This requires first developing efficient interfaces between photons and multiqubit registers. In this Letter, we show how to entangle each individual matter qubit in a register of ten to a separate traveling photon. The qubits are encoded in a string of cotrapped atomic ions. By switching the trap confinement, ions are brought one at a time into the waist of an optical cavity and emit a photon via a laser-driven cavity-mediated Raman transition. The result is a train of photonic qubits, each near-maximally entangled by their polarization with a different ion qubit in the string. An average ion-photon Bell state fidelity of 92% is achieved, for an average probability for detecting each single photon of 9%. The technique is directly scalable to larger ion-qubit registers and opens up the near-term possibility of entangling distributed networks of trapped-ion quantum processors, sensing arrays, and clocks.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".