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.
On the Yang-Mills wave functional in Coulomb gauge
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abstract
We investigate the dependence of the Yang-Mills wave functional in Coulomb gauge on the Faddeev-Popov determinant. We use a Gaussian wave functional multiplied by an arbitrary power of the Faddeev-Popov determinant. We show, that within the resummation of one-loop diagrams the stationary vacuum energy is independent of the power of the Faddeev-Popov determinant and, furthermore, the wave functional becomes field-independent in the infrared, describing a stochastic vacuum. Our investigations show, that the infrared limit is rather robust against details of the variational ans\"atze for the Yang-Mills wave functional. The infrared limit is exclusively determined by the divergence of the Faddeev-Popov determinant at the Gribov horizon.
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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.