B06

The main challenge in Lattice Quantum Chromodynamics (LQCD) computations is efficiently solving large sparse linear systems of the form Dz = b, where D depends on a gauge field U and a mass constant m. Current simulation methods spend more than 90% of the computational time on this task, making it crucial to develop more efficient scalable linear solvers for LQCD. This project aims to develop a robust and efficient linear solver using novel algebraic multigrid / algebraic multiscale techniques and integrating Machine Learning (ML) techniques into the solver setup.