High-Resolution Imaging of Cold Atoms through a Multimode Fiber
Bibliographic record
Abstract
We develop an ultracompact high-resolution imaging system for cold atoms. Its only in-vacuum element is a multimode optical fiber with a diameter of 230 $\ensuremath{\mu}\mathrm{m}$, which simultaneously collects light and guides it out of the vacuum chamber. External adaptive optics allow us to image cold $\mathrm{Rb}$ atoms with approximately 1-$\ensuremath{\mu}\mathrm{m}$ resolution over a $100\ifmmode\times\else\texttimes\fi{}100\phantom{\rule{0.2em}{0ex}}\ensuremath{\mu}{\mathrm{m}}^{2}$ field of view. These optics can be easily rearranged to switch between fast absorption imaging and high-sensitivity fluorescence imaging. This system is particularly suited for hybrid quantum-engineering platforms where cold atoms are combined with optical cavities, superconducting circuits, or optomechanical devices restricting optical access.
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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 | 0.001 | 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) | 0.001 | 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".