  This brief review introduces the reader to tensor network methods, a powerful
theoretical and numerical paradigm spawning from condensed matter physics and
quantum information science and increasingly exploited in different fields of
research, from artificial intelligence to quantum chemistry. Here, we
specialise our presentation on the application of loop-free tensor network
methods to the study of High-Energy Physics (HEP) problems and, in particular,
to the study of lattice gauge theories where tensor networks can be applied in
regimes where Monte Carlo methods are hindered by the sign problem.
