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Record W2015438802 · doi:10.1142/s0219633604001148

LINEAR SCALING FOR DENSITY FUNCTIONAL CALCULATIONS ON LARGE MOLECULES WITH THE DEFT SOFTWARE PACKAGE

2004· article· en· W2015438802 on OpenAlexafffund
D. M. Shaw, Alain St‐Amant

Bibliographic record

VenueJournal of Theoretical and Computational Chemistry · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsScalingBenchmark (surveying)Linear scaleDivide and conquer algorithmsSoftwareComputer scienceBasis (linear algebra)Density functional theorySoftware packageAlgorithmStatistical physicsComputational physicsComputational sciencePhysicsMathematicsComputational chemistryChemistryGeometry

Abstract

fetched live from OpenAlex

The new methods implemented within the DeFT density functional software package are outlined. Where appropriate, they are benchmarked against the conventional methods, which are prohibitively expensive for large systems due to their poor scaling with system size. Benchmark calculations on extended glycine polypeptides clearly demonstrate that linear scaling has been achieved for these first principles electronic structure calculations. Within the DeFT software package, a divide-and-conquer approach is instrumental in attaining this goal. The errors introduced by our divide-and-conquer approach are quantified and shown to be insignificant when compared to the inherent error in even the most accurate density functionals presently available. Calculations on molecules within the G2 dataset highlight the overall accuracy of the exchange-correlation functionals, orbital basis sets, auxiliary density fitting basis sets, and grids used within DeFT.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.203

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 head0.006
GPT teacher head0.236
Teacher spread0.230 · 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

Citations17
Published2004
Admission routes2
Has abstractyes

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