1 citations · 1 across the 1 of their papers we have counts for
4 papers
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…
Fixed point actions from convolutional neural networks
Kieran Holland, Andreas Ipp, David I. Müller +1
Lattice gauge-equivariant convolutional neural networks (L-CNNs) can be used to form arbitrarily shaped Wilson loops and can approximate any gauge-covariant or gauge-invariant func…