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Mean-field theory

In physics and probability theory, mean-field theory (MFT) or self-consistent field theory studies the behavior of high-dimensional random (stochastic) models by studying a simpler model that approximates the original by averaging over degrees of freedom (the number of values in the final calculation of a statistic that are free to vary). Such models…

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Overview

Origins

Validity

Formal approach (Hamiltonian)

Applications

Extension to time-dependent mean fields

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Mean-field theory

Nodes74
Edges73
Triples8
Avg. degree1.97
Density0.027027
Components1

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Mean-field theory

Top relations

related to Formal approach (Hamiltonian) · 4
Mean-field theory → Bogoliubov, Hamiltonian, The, This
is a · 1
Mean-field theory → Bogoliubov inequality

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Important terminology

displaystyle field mean hamiltonian mft system theory function effective approximation fluctuations spins ising model spin number free one models interactions

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Mean-field theoryis aBogoliubov inequality0.90text
phase transitions.Ising modelFormal derivationThe Bogoliubov inequalityinstance ofApplicationsMean field theory can be applied to a number of physical systems so as to study phenomena0.80text
shown aboveinstance ofApplicationsMean field theory can be applied to a number of physical systems so as to study phenomena0.80text
can be used to find the dynamics of a mean field model of the two-dimensional Ising latticeinstance ofApplicationsMean field theory can be applied to a number of physical systems so as to study phenomena0.80text
Mean-field theoryrelated to Formal approach (Hamiltonian)The0.60section
Mean-field theoryrelated to Formal approach (Hamiltonian)Bogoliubov0.60section
Mean-field theoryrelated to Formal approach (Hamiltonian)This0.60section
Mean-field theoryrelated to Formal approach (Hamiltonian)Hamiltonian0.60section

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    Min side: 3
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