A linear array of 11 double-loop microtraps for ultracold atoms
Bibliographic record
Abstract
A linear array of 11 closely spaced microtraps was demonstrated. Each microtrap was created using the magnetic field generated by two concentric circular wire loops having radii of 60 and 132 μm carrying oppositely oriented currents as well as a bias magnetic field oriented perpendicular to the atom chip surface containing the microwire loops. 87Rb atoms were initially cooled using either a surface magneto-optical trap (MOT) or a far off resonance optical dipole trap (FORT) created using an infrared laser directed along the microtrap array axis. The microtrap current was turned on and over 12 000 atoms were loaded into each microtrap. The advantage of FORT loading was that the 11 microtraps were about equally populated and the microtrapped atom temperature of 11 μK was one quarter of that obtained using the MOT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 teacher head, 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".