4 papers
Machine learning for four-dimensional SU(3) lattice gauge theories
Urs Wenger
In this review I summarize how machine learning can be used in lattice gauge theory simulations and what ap\-proaches are currently available to improve the sampling of gauge field…
Machine-learned RG-improved gauge actions and classically perfect gradient flows
Kieran Holland, Andreas Ipp, David I. Müller +1
Extracting continuum properties of quantum field theories from discretized spacetime is challenging due to lattice artifacts. Renormalization-group (RG)-improved lattice actions ca…
HMC and gradient flow with machine-learned classically perfect fixed-point actions
Kieran Holland, Andreas Ipp, David I. Müller +1
Fixed-point (FP) lattice actions are classically perfect, i.e., they have continuum classical properties unaffected by discretization effects and are expected to have suppressed la…
Machine learning a fixed point action for SU(3) gauge theory with a gauge equivariant convolutional neural network
Kieran Holland, Andreas Ipp, David I. Müller +1
Fixed point lattice actions are designed to have continuum classical properties unaffected by discretization effects and reduced lattice artifacts at the quantum level. They provid…