Optically accessible high-finesse millimeter-wave resonator for cavity quantum electrodynamics with atom arrays
Bibliographic record
Abstract
Cavity quantum electrodynamics (QED) is a powerful tool in quantum science, enabling preparation of nonclassical states of light and scalable entanglement of many atoms coupled to a single field mode. While the most coherent atom-photon interactions have been achieved using superconducting millimeter-wave cavities coupled to Rydberg atoms, these platforms so far lack the optical access required for trapping and addressing individual atomic qubits. We present a millimeter-wave Fabry-Pérot cavity with finesse <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mn>5.8</a:mn> <a:mo stretchy="false">(</a:mo> <a:mn>1</a:mn> <a:mo stretchy="false">)</a:mo> <a:mo>×</a:mo> <a:msup> <a:mn>10</a:mn> <a:mn>7</a:mn> </a:msup> </a:math> at a temperature of 1 K providing generous transverse optical access (numerical aperture 0.56). Conflicting goals of strong atom-photon coupling and optical access motivate a near-confocal geometry. Close to confocality, however, postparaxial corrections to the cavity spectrum introduce unexpected degeneracies between transverse modes, leading to excess cavity loss. Modeling these corrections allows for tuning the cavity geometry to evade this loss, producing a high finesse that will enable cavity QED experiments with trapped atoms deep in the strong coupling regime.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".