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Record W2332159087 · doi:10.1103/physreva.86.052518

Self-interaction correction scheme for approximate Kohn-Sham potentials

2012· article· en· W2332159087 on OpenAlexafffund
Alex P. Gaiduk, Dan Mizzi, Viktor N. Staroverov

Bibliographic record

VenuePhysical Review A · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsKohn–Sham equationsRydberg formulaAtomic physicsExcitationDensity functional theoryEigenvalues and eigenvectorsElectronQuantum mechanicsIonizationState (computer science)Ion

Abstract

fetched live from OpenAlex

Recently [Phys. Rev. Lett. 108, 253005 (2012)], we observed that approximate Hartree-exchange-correlation potentials constructed from electron densities depleted at the highest-occupied molecular orbital (HOMO) level mimic the exact potential at intermediate distances from the nuclei; we then used this fact to obtain accurate Rydberg excitation energies of atoms and molecules within time-dependent density-functional linear-response theory employing standard semilocal approximations. Here we reinterpret this method as a form of self-interaction correction for Kohn-Sham potentials. We show that the greatest improvement in HOMO eigenvalues occurs when the charge removed from the HOMO level is about $\frac{1}{2}$ electron, which explains why the Slater transition-state method works well for predicting ionization energies. The greatest improvement in Kohn-Sham orbital gaps, however, is achieved when about $\frac{1}{4}$ electron is removed, which is why smaller HOMO depopulations are required for obtaining accurate excitation energies. The relationship between our self-interaction correction scheme, Slater's transition-state technique, and the $X\ensuremath{\alpha}$ method is also clarified.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.745
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.340
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2012
Admission routes2
Has abstractyes

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