Ab initio calculation of atomic ground state energies using the in-medium similarity renormalization group
Bibliographic record
Abstract
Computational many-body physics presents one of the most difficult challenges for theoretical physics.In order to solve many-body physics problems, we consider several choices of basis functions, and describe how to determine matrix elements in each basis for the atomic Hamiltonian evolved in the In-Medium Similarity Renormalization Group.Our results demonstrate that the Laguerre basis functions demonstrate an excellent basis, and we are able to calculate ground state energies of several Noble gases with extreme precision.The results of this research can further be built upon to create a tool for prediction of both nuclear and atomic physics properties ab initio. 1 Abstrait Résoudre un problème à N corps s'avère être un des plus grands défis en physique théorique.Pour résoudre un tel problème, nous considérons plusieurs choix de fonctions de base et décrivons comment déterminer les éléments de l'Hamiltonien de l'atome dans chaque base après que celles-ci aient été évoluées à l'aide du "In-Medium Similarity Renormalization Group".Nos résultats montrent que la base des fonctions de Laguerre est un excellent choix.De plus, nous avons pu calculer l'énergie de l'état fondamental de plusieurs gas nobles avec une très grande précision.Les résultats de cette recherche peuvent servir d'assise pour la création d'un outil pouvant prédire tant les propriétés nucléaires qu'atomiques ab initio.7.12 Hartree-Fock and IM-SRG calculations of the ground state of krypton as a function of the truncation parameter, E max , and the length parameter, b.Dark blue indicates E max =2, cyan is E max =4, increasing in increments of 2, with purple being the highest at E max =12. . . . . . . . . . . . . . . . . . . .57 7.13 Hartree-Fock and IM-SRG calculations of the ground state of xenon as a function of the truncation parameter, E max , and the length parameter, b.Dark blue indicates E max =2, cyan is E max =4, increasing in increments of 2, with purple being the highest at E max =12. . . . . . . . .
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".