Bibliographic record
Abstract
I detail the construction of an experimental apparatus created for performing ultracold atomic experiments with fermionic lithium-6 (Li) and several isotopes of ytterbium (Yb), and several of the rst experiments performed using this apparatus.The apparatus consists of a vacuum chamber, laser and auxiliary systems, which together are used to produce the rst instance of trapped ultracold mixtures of lithium and ytterbium.We show that the system is stable and obtain the s-wave scattering properties of Li-Yb collisions.By using Yb to sympathetically cool Li, double quantum degeneracy is achieved.I demonstrate the versatility of the new system with several experiments.In the rst, we investigate the behvaiour of Li near a broad Feshbach resonance, and modify it with Yb.In the second, we produce Yb in the metastable state, and trap it in a 1064 nm optical dipole trap, which allows for a technically simple spin polarization procedure.We then characterize the dynamics of a Li -metastable Yb mixture.The work described in this thesis provides a pathway to future extensions such as the magentic tuning of Li-Yb interactions and the production of LiYb molecules by either photoor magnetoassociation.The potential interest of this specic system lies in the combination of alkali and spin-singlet atom, leading to a potential paramagnetic ground state molecule, and experimental realizations of systems which cannot be accessed with bialkali experiments.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".