Direct extraction of nuclear structure information using precision lithium-ion spectroscopy
Bibliographic record
Abstract
Accurately describing nuclear interactions within atomic nuclei remains a challenge, which hinders our exploration of new physics beyond the Standard Model. However, these nuclear interactions can be characterized by nuclear parameters such as the Zemach radius and the electric quadrupole moment, which are reflected in atomic spectra. Our work has achieved high-precision measurements of lithium ion hyperfine splittings at the level of $10$~kHz, and directly extracted these important nuclear structure parameters. We observed significant discrepancies between our results and both nuclear theory and molecular spectra regarding the electric quadrupole moment. The result for $^7$Li deviated by $2.3σ$ from the currently recommended value, whereas the result for $^6$Li deviated by up to $6.2σ$ from the recommended value determined by molecular spectroscopy. These discrepancies motivated us to conduct independent calculations based on nuclear structure theory, which provided support for the results obtained from ion spectroscopy. Our results provide valuable information for characterizing nuclear forces, serve as sensitive benchmarks for testing nuclear structure theories, and enable critical comparisons with both electron-nuclear scattering and molecular spectroscopy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".