Tensor network based integration methods

Abstract

In this work we overview the Tensor Train Cross decomposition of large tensors and its applicability to high-dimensional integration. Furthermore, two different algorithms for building this decomposition are showcased and compared against a Monte Carlo method, both outperforming it in terms of resource efficiency. A python package is also presented, containing these two algorithms along other tools to leverage the power of the framework in a comprehensive and easy to use manner