2 papers
hep-lat2026
A novel gauge-equivariant neural-network architecture for preconditioners in lattice QCD
Simon Pfahler, Daniel Knüttel, Christoph Lehner +1
Lattice QCD simulations are computationally expensive, with the solution of the Dirac equation being the major computational bottleneck of many calculations. We introduce a novel g…
stat.CO2024
Taming numerical imprecision by adapting the KL divergence to negative probabilities
Simon Pfahler, Peter Georg, Rudolf Schill +4
The Kullback-Leibler (KL) divergence is frequently used in data science. For discrete distributions on large state spaces, approximations of probability vectors may result in a few…