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Record W1978377647 · doi:10.1080/08927020008023008

The Implementation of the Iterative Diagonalization Scheme and<i>ab initio</i>Molecular Dynamics Simulation with the LAPW Method

2000· article· en· W1978377647 on OpenAlexafffund
Kentaro Uehara, John S. Tse

Bibliographic record

VenueMolecular Simulation · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsSteacie Institute for Molecular Sciences
FundersNatural Sciences and Engineering Research Council of CanadaNational Parks and Wildlife Service
KeywordsBasis setBasis (linear algebra)Diatomic moleculeAb initioElectronic structureWave functionSimple (philosophy)Plane waveBasis functionResidualPhysicsQuantum mechanicsComputer scienceMathematicsMoleculeAlgorithmGeometry

Abstract

fetched live from OpenAlex

A new ab initio molecular dynamics method based on the full-potential linearized-augmented-plane-wave (LAPW) basis set has been implemented. The LAPW basis set has been successfully employed for systems containing localized electrons such as first row atoms and transition metals. In our implementation of the LAPW-MD scheme, iterative residual minimization algorithm is used to solve the electronic states problem. The atoms are moved according to forces derived from the Hellman–Feynman theorem and incomplete basis set correction terms. The performance of the program is further enhanced by parallelization. We will discuss technical details of the program implementation and present results obtained from this code to the equilibrium structures and vibrational properties of simple diatomic molecules.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.005
GPT teacher head0.301
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2000
Admission routes2
Has abstractyes

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