Tensor-network-based machine learning of non-Markovian quantum processes
Tensor-network-based machine learning of non-Markovian quantum processes
We show how a tensor-network-based machine learning algorithm can learn the structures of generic, non-Markovian, quantum stochastic processes. First, a process is represented as a matrix product operator (MPO) and trained with a database of local input states at different times and the corresponding time-nonlocal output state. We then apply …