1 citations · 1 across the 2 of their papers we have counts for
4 papers
Approximating Grassmann-valued Path Integrals with Radial Basis Function Neural Networks
Gabor Balassa
Solving path integrals in quantum field theories often involves the numerical handling of noncommuting Grassmann fields, which is in many cases a highly nontrivial and numerically…
Neural network expansion of Euclidean path integrals and its application to interacting scalar fields
Gabor Balassa
Studying phase transitions in interacting quantum field theories generally requires the numerical study of the dynamical system on a large lattice, which is, in most cases, computa…
On the solution of Euclidean path integrals with neural networks
Gabor Balassa
This paper proposes a numerical method using neural networks to solve the path integral problem in quantum mechanics for arbitrary potentials. The method is based on a radial basis…
Addressing the sign-problem in Euclidean path integrals with radial basis function neural networks
Gabor Balassa
Solving interacting field theories at finite densities remains a numerically and conceptually challenging task, even with modern computational capabilities. In this paper, we propo…