A variational neural network ansatz approximates the ground-state wavefunctional of the free Klein-Gordon theory in momentum-space field basis and is validated against exact analytic observables.
A variational approach to the QCD wave functional:Dynamical mass generation and confinement
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abstract
We perform a variational calculation in the SU(N) Yang Mills theory in 3+1 dimensions. Our trial variational states are explicitly gauge invariant, and reduce to simple Gaussian states in the zero coupling limit. Our main result is that the energy is minimized for the value of the variational parameter away form the perturbative value. The best variational state is therefore characterized by a dynamically generated mass scale $M$. This scale is related to the perturbative scale $\Lambda_{QCD}$ by the following relation: $\alpha_{QCD}(M)={\pi\over 4}{1\over N}$. Taking the one loop QCD $\beta$- function and $\Lambda_{QCD}=150 Mev$ we find (for N=3) the vacuum condensate ${\alpha\over \pi}<F^2>= 0.008 Gev^4$.
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Variational Neural Network Approach to QFT in the Field Basis
A variational neural network ansatz approximates the ground-state wavefunctional of the free Klein-Gordon theory in momentum-space field basis and is validated against exact analytic observables.