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arXiv · 2004.10892

Simple heuristics for efficient parallel tensor contraction and quantum circuit simulation

Roman Schutski·Dmitry Kolmakov·Taras Khakhulin·Ivan Oseledets
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Abstract

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 $\mu$-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.

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Roman Schutski, Dmitry Kolmakov, Taras Khakhulin, Ivan Oseledets. 2020-04-22. Simple heuristics for efficient parallel tensor contraction and quantum circuit simulation. https://doi.org/10.1103/physreva.102.062614

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