Properties of magnetic sublevel coherences for precision measurements
Bibliographic record
Abstract
We have developed a theoretical description of the evolution of ground state coherences between magnetic sublevels in Rb vapor in the presence of a magnetic field along an arbitrary direction. This formalism uses a rotation matrix approach to describe the evolution of coherences created by two traveling wave laser pulses with orthogonal polarizations. The effect of a magnetic field can be described as a time-dependent rotation of the atomic system about the quantization axis. Predictions based on this theoretical formalism for the functional form of Larmor oscillations in a magnetic field are studied using a coherent transient effect known as magnetic grating free induction decay (MGFID) using room temperature vapor and laser cooled atoms. We find the theoretical predictions to be in excellent agreement with data. The velocity distribution of the cold sample measured from the dephasing time of the MGFID in the absence of magnetic fields is in agreement with the sample temperature obtained by imaging the ballistic expansion of the trapped cloud. By using rate equations to model atomic coherences, it is also possible to predict the evolution of magnetic grating echoes (MGE) in a magnetic field. We compare these predictions with experiments from cold atoms and discuss applications of the MGFID and MGE that relate to a precision measurement of the atomic $g$ factor ratio using $^{85}\mathrm{Rb}$ and $^{87}\mathrm{Rb}$ isotopes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".