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Record W2087825804 · doi:10.1002/cphc.200400381

Dynamic Evolution of Kohn–Sham Electron Density in the Real‐Time Domain with Finite Basis Expansion

2005· article· en· W2087825804 on OpenAlexafffund
Anguang Hu, Tom K. Woo

Bibliographic record

VenueChemPhysChem · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaOntario Innovation Trust
KeywordsDensity functional theoryHOMO/LUMOCharge (physics)Interpolation (computer graphics)ChemistryElectron densityLinear interpolationBasis (linear algebra)ElectronTime domainPhysicsMoleculeStatistical physicsQuantum mechanicsComputational chemistryClassical mechanicsMathematical analysisMathematicsGeometryComputer science

Abstract

fetched live from OpenAlex

We present a novel method for time-dependent density functional theory calculations on dynamic linear response and electron density evolution in the real-time domain with the finite basis expansion approach of conventional quantum chemistry. To demonstrate the validity and efficiency of this method, dynamic polarizabilities of a water chain and diphenylene molecules are computed by employing the Chebyshev interpolation algorithm, which was developed by Baer and co-workers. The calculated dynamic polarizabilities show good agreement with those obtained from conventional linear response calculations. The density evolution in the real-time domain with application of a long-duration electric field gives electronic conduction in molecules, where a dynamic process of charge transfer is observed with the snapshots of response density in real time. Charge transfer oscillating with the frequency of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) gap is shown in a diphenylene molecule while there is little change in time for a water chain.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.474

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 head0.004
GPT teacher head0.225
Teacher spread0.220 · 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 designBench or experimental
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

Citations3
Published2005
Admission routes2
Has abstractyes

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