Simple heuristics for efficient parallel tensor contraction and quantum circuit simulation

04/22/2020
by   Roman Schutski, et al.
0

Tensor networks are the main building blocks in a wide variety of computational sciences, ranging from many-body theory and quantum computing to probability and machine learning. Here we propose a parallel algorithm for the contraction of tensor networks using probabilistic graphical models. Our approach is based on the heuristic solution of the μ-treewidth deletion problem in graph theory. We apply the resulting algorithm to the simulation of random quantum circuits and discuss the extensions for general tensor network contractions.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset