Performance of the Harris functional for extended basis sets at the Hartree–Fock and density functional levels
Bibliographic record
Abstract
The Harris functional is a noniterative variational procedure that uses an input charge density to produce an energy that is surprisingly accurate compared to the converged Kohn-Sham self-consistent result. We adapted and generalized this functional for the Hartree-Fock closed- and open-shell cases as well as examined its use for hybrid density functional methods such as B3LYP. Analysis of extended basis set calculations shows that at the B3LYP level an input density formed from a double zeta + polarization orbital basis is accurate enough to reproduce the energy of triple zeta + double polarization + diffuse orbital basis. For large molecules this translates into a computational speed that can be an order of magnitude faster. In the case of Hartree-Fock calculations a "bootstrapping technique" that employs successive applications of the Harris functional can further reduce computational times while retaining sufficient accuracy.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".