An extremely efficient and rapid algorithm for numerical evaluation of three-centre nuclear attraction integrals over Slater-type functions
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Bibliographic record
Abstract
The present work concerns the development of an extremely accurate and rapid algorithm for the numerical evaluation of the three-centre nuclear attraction integrals over Slater-type functions. These integrals are numerous, they occur in many millions of terms, even for small molecules and they require rapid and accurate evaluation. The new algorithm is based on nonlinear transformation methods, on numerical quadrature and on properties of the sine and Bessel functions. The section with numerical results shows the high accuracy and the substantial gain in calculation time realized using the new algorithm. The complete expressions of the three-centre nuclear attraction integrals over B functions and over Slater-type functions are evaluated for different values of the quantum numbers to show the efficiency of the new approach. Numerical results obtained with linear and nonlinear systems and comparisons with numerical results from the literature are listed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it