Tree tensor network state approach for solving hierarchical equations of motion

Abstract

The hierarchical equations of motion (HEOM) method is a numerically exact open quantum system dynamics approach. The method is rooted in an exponential expansion of the bath correlation function, which in essence strategically reshapes a continuous environment into a set of effective bath modes that allow for more efficient cutoff at finite temperatures. Based on this understanding, one can map the HEOM method into a Schr\"odinger-like equation with a non-Hermitian super Hamiltonian for an extended wavefunction being the tensor product of the central system wave function and the Fock state of these effective bath modes. Recognizing that the system and these effective bath modes form a star-shaped entanglement structure, in this work, we explore the possibility of representing the extended wave function as an efficient tree tensor network state (TTNS), the super Hamiltonian as a tree tensor network operator of the same structure, as well as the application of a time propagation algorithm using the time-dependent variational principle. Our benchmark calculations based on the spin-boson model with a slow-relaxing bath show that, the proposed HEOM+TTNS approach yields consistent results with that of the conventional HEOM method, while the computation is considerably sped up by a factor of a few orders of magnitude. Besides, the simulation with a genuine TTNS is four times faster than a one-dimensional matrix product state decomposition scheme.