Spectrum of Feshbach Resonances in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>Na</mml:mi><mml:mrow><mml:mi>Li</mml:mi><mml:mo stretchy="false">+</mml:mo></mml:mrow><mml:mi>Na</mml:mi></mml:mrow></mml:math> Collisions
Bibliographic record
Abstract
Collisional resonances of molecules can offer a deeper understanding of interaction potentials and collision complexes, and allow control of chemical reactions.Here, we experimentally map out the spectrum of Feshbach resonances in collisions between ultracold triplet rovibrational ground-state NaLi molecules and Na atoms over a range of 1400 G. Preparation of the spin-stretched state puts the system initially into the nonreactive quartet potential.A total of 25 resonances are observed, in qualitative agreement with quantum-chemistry calculations using a coupled-channels approach.Although the theory cannot predict the positions of resonances, it can account for several experimental findings and provide unprecedented insight into the nature and couplings of ultracold, strongly interacting complexes.Previous work has addressed only weakly bound complexes.We show that the main coupling mechanism results from spin-rotation and spin-spin couplings in combination with the anisotropic atom-molecule interaction, and that the collisional complexes which support the resonances have a size of 30a 0 -40a 0 .This study illustrates the potential of a combined experimental and theoretical approach.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.107 | 0.005 |
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".