Simulating exact quantum dynamics of a low-dimensional system interacting with a large dissipative environment proves to be challenging due to presence of non-Markovian effects. Tensor networks can be successfully used to reduce the memory burden of these non-Markovian simulations making it possible to study chemical reactions in the condensed phase with greater accuracy.
