Faddeev calculation of 3 alpha and alpha alpha Lambda systems using alpha alpha resonating-group method kernels
Bibliographic record
Abstract
We carry out Faddeev calculations of three-alpha $(3\ensuremath{\alpha})$ and two-alpha plus $\ensuremath{\Lambda}$ $(\ensuremath{\alpha}\ensuremath{\alpha}\ensuremath{\Lambda})$ systems, using two-cluster resonating-group method kernels. The input includes an effective two-nucleon force for the $\ensuremath{\alpha}\ensuremath{\alpha}$ resonating-group method and a new effective $\ensuremath{\Lambda}N$ force for the $\ensuremath{\Lambda}\ensuremath{\alpha}$ interaction. The latter force is a simple two-range Gaussian potential for each spin-singlet and triplet state, generated from the phase-shift behavior of the quark-model hyperon-nucleon interaction, fss2, by using an inversion method based on supersymmetric quantum mechanics. Owing to the exact treatment of the Pauli-forbidden states between two $\ensuremath{\alpha}$ clusters, the present three-cluster Faddeev formalism can describe the mutually related, $\ensuremath{\alpha}\ensuremath{\alpha}$, $3\ensuremath{\alpha}$, and $\ensuremath{\alpha}\ensuremath{\alpha}\ensuremath{\Lambda}$ systems, in terms of a unique set of the baryon-baryon interactions. For the three-range Minnesota force which describes the $\ensuremath{\alpha}\ensuremath{\alpha}$ phase shifts quite accurately, the ground-state and excitation energies of $_{\ensuremath{\Lambda}}^{9}\mathrm{Be}$ are reproduced within $100--200\phantom{\rule{0.3em}{0ex}}\mathrm{keV}$ accuracy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".