Correlations in many electron systems: theory and applications
Bibliographic record
Abstract
In this contribution, we present calculations performed for interacting electron systems within a nonperturbative formulation of the cluster theory. Extrapolation of the model to describe the time dependence of the interacting systems is feasible and planned. The theory is based on the unitary operator eiS (S is the correlation operator) formalism which, in this paper, is treated non perturbatively within many-particle correlations. The application of the derived equations to few-body systems is realized in terms of generalized linearization approximations and via the cluster factorization theory. To check the reliability of the model, we present two different applications. In the first, we evaluate the transitions energies in helium-, lithium-, beryllium-, and boron-like oxygen. The calculation aims for a precise determination of the satellite transitions that play an important role in plasma diagnostics. In the second application we investigate a nonperturbative method to evaluate the charge radii of the helium and lithium isotopes by using the isotopic shift theory. We found that our model leads naturally to components of e––e+ pair in the two-electron wave functions of the helium isotopes and three-electron wave functions of the lithium isotopes. The possible connection of these terms to the quantum electrodynamics leading diagrams is postulated.PACS Nos.: 31.10.+z, 31.30.Gs, 32.30.–r
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".