  WaveTrain is an open-source software for numerical simulations of chain-like
quantum systems with nearest-neighbor (NN) interactions only. The Python
package is centered around tensor train (TT, or matrix product) format
representations of Hamiltonian operators and (stationary or time-evolving)
state vectors. It builds on the Python tensor train toolbox Scikit-tt, which
provides efficient construction methods and storage schemes for the TT format.
Its solvers for eigenvalue problems and linear differential equations are used
in WaveTrain for the time-independent and time-dependent Schroedinger
equations, respectively. Employing efficient decompositions to construct
low-rank representations, the tensor-train ranks of state vectors are often
found to depend only marginally on the chain length N. This results in the
computational effort growing only slightly more than linearly with N, thus
mitigating the curse of dimensionality. As a complement to the classes for full
quantum mechanics, WaveTrain also contains classes for fully classical and
mixed quantum-classical (Ehrenfest or mean field) dynamics of bipartite
systems. The graphical capabilities allow visualization of quantum dynamics on
the fly, with a choice of several different representations based on reduced
density matrices. Even though developed for treating quasi one-dimensional
excitonic energy transport in molecular solids or conjugated organic polymers,
including coupling to phonons, WaveTrain can be used for any kind of chain-like
quantum systems, with or without periodic boundary conditions, and with NN
interactions only.
