Chiral two- and three-nucleon forces along medium-mass isotope chains
Bibliographic record
Abstract
Ab initio calculations have shown that chiral two- and three-nucleon interactions correctly reproduce binding energy systematics and neutron drip lines of oxygen and nearby isotopes. Exploiting the novel Gorkov-Green's function approach applicable to genuinely open-shell nuclei, we present the first $ab$ initio investigation of Ar, K, Ca, Sc, and Ti isotopic chains. In doing so, stringent tests of internucleon interaction models are provided in the medium-mass region of the nuclear chart. Leading chiral three-nucleon interactions are shown to be mandatory to reproduce the trend of binding energies throughout these chains and to obtain a good description of two-neutron separation energies. At the same time, nuclei in this mass region are systematically overbound by about 40 MeV. While the fundamental $N=20$ and 28 magic numbers do emerge from basic internucleon interactions, the former is shown to be significantly overestimated, which points to deficiencies of state-of-the-art chiral potentials. The present results demonstrate that ab initio many-body calculations can now access entire medium-mass isotopic chains including degenerate open-shell nuclei and provide a critical testing ground for modern theories of nuclear interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".