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Record W2883107923

N-Representability in the Quantum Kernel Energy Method

2018· article· en· W2883107923 on OpenAlexfundno aff
Walter Polkosnik

Bibliographic record

VenueCUNY Academic Works (City University of New York) · 2018
Typearticle
Languageen
FieldChemistry
TopicAdvanced Physical and Chemical Molecular Interactions
Canadian institutionsnot available
FundersU.S. Naval Research LaboratoryNatural Sciences and Engineering Research Council of CanadaOffice of Naval ResearchMount Saint Vincent University
KeywordsKernel (algebra)QuantumEnergy (signal processing)Computer scienceMathematicsPhysicsQuantum mechanicsDiscrete mathematics
DOInot available

Abstract

fetched live from OpenAlex

The Kernel Energy Method (KEM) delivers accurate full molecule energies using less computational resources than standard ab-initio quantum chemical approaches. KEM achieves this efficiency by decomposing a system of atoms into disjoint subsets called kernels. The results of full ab-initio calculations on each individual single kernel and on each double kernel formed by the union of each pair of single kernels are combined in an equation of a form that is specific to KEM to provide an approximation to the full molecule energy. KEM has been demonstrated to give accurate molecular energies over a wide range of systems, chemical methods and basis sets. The efficiency of KEM makes calculations on large systems tractable. It has been shown to be accurate for calculations on large biomolecules including proteins and DNA. KEM has recently been generalized to provide the one-body density matrix for the full molecule. This generalization greatly expands the utility of the method since the density matrix enables simple calculation of the expectation value of any observable associated with a one-body operator. More importantly, the generalization enables results from KEM to be constrained to satisfy essential quantum mechanical conditions. KEM is generalized to density matrices by taking the density matrices obtained from the single and double kernels and adapting them to the full molecule basis. These augmented kernel density matrices are summed according to the standard KEM expansion. This initial matrix does not necessarily correspond to a valid quantum mechanical N-electron wavefunction which is normalized and obeys the Pauli principle. Such a density matrix is called N-representable. N-representability is imposed on the initial matrix by using the Clinton equations, which deliver a single-determinant N-representable one-body density matrix. Single-determinant N-representability is ensured by enforcing the density matrix to be a normalized projector. Such normalized projectors are factorizable into matrices which deliver full molecule molecular orbitals. Although energies have been demonstrated to be accurate in the original energy expansion form of KEM, there is no requirement that the energy corresponds to the expectation value of a valid quantum mechanical wavefunction. Because of this, there is no requirement that the energies satisfy the variational theorem. Imposing single-determinant N-representability on the KEM density matrix by using the Clinton equations recovers the variational bound on the energy obtained from KEM. Recovery of the variational bound by the N-representable KEM density matrix has been demonstrated by calculations on several water clusters. Energies from full molecule restricted Hartree-Fock calculations were compared to energies obtained from the KEM energy expansion and to energies obtained from the KEM density matrix expansion which had N-representability imposed. In each case where the energy expansion gave energies that violated the variational bound the N-representable density matrix gave energies that satisfied the bound and in fact were more accurate than the simple energy expansion results. The effect of imposing N-representability on the KEM density matrix has also been investigated in the context of Kohn-Sham Density Functional Theory (KS/DFT). Calculations on a simple noble gas system and a single water cluster were done. KS/DFT energies were compared to energies from the KEM energy expansion and energies associated with the KEM density matrix expansion on which N-representability was imposed. The energies from the KEM density matrix expansion made N-representable were more accurate than those obtained from straightforward KEM energy expansions in nearly all cases for the noble gas system. For the water cluster the accuracy of the energy obtained from the N-representable KEM density matrix was nearly four times closer to the energy calculated for the full system than the KEM energy expansion result. The Clinton-purified N-representable matrix obtained from the KEM density expansion can be used to calculate expectation values for any one-electron operator. In particular, a KEM density matrix approach can be used in the study of quantum crystallography.

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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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.291
Teacher spread0.256 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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