12 citations · 13 across the 4 of their papers we have counts for
8 papers · 1 filter
Learning Trivializing Flows
David Albandea, Luigi Del Debbio, Pilar Hernández +3
The recent introduction of Machine Learning techniques, especially Normalizing Flows, for the sampling of lattice gauge theories has shed some hope on improving the sampling effici…
Learning trivializing flows
David Albandea, Luigi Del Debbio, Pilar Hernández +3
The recent introduction of machine learning techniques, especially normalizing flows, for the sampling of lattice gauge theories has shed some hope on improving the sampling effici…
A lattice study of scattering at large
Jorge Baeza-Ballesteros, Pilar Hernández, Fernando Romero-López
We present the first lattice study of pion-pion scattering with varying number of colors, . We use lattice simulations with four degenerate quark flavors, $N_\text{f}=4…
Improved topological sampling for lattice gauge theories
David Albandea, Pilar Hernández, Alberto Ramos +1
Standard sampling algorithms for lattice QCD suffer from topology freezing (or critical slowing down) when approaching the continuum limit, thus leading to poor sampling of the dis…
Topological sampling through windings
David Albandea, Pilar Hernández, Alberto Ramos +1
We propose a modification of the Hybrid Monte Carlo (HMC) algorithm that overcomes the topological freezing of a two-dimensional gauge theory with and without fermion conten…
Dissecting the rule at large
Andrea Donini, Pilar Hernández, Carlos Pena +1
We study the scaling of kaon decay amplitudes with the number of colours, , in a theory with four degenerate flavours, . In this scenario, two current-current operators…