TensorNetwork on TensorFlow: A Spin Chain Application Using Tree Tensor Networks (2019-05-03T00:00:00.000000Z)

TL;DR

This work describes a tree tensor network (TTN) algorithm for approximating the ground state of either a periodic quantum spin chain or a lattice model on a thin torus, and implements the algorithm using TensorNetwork.

Abstract

TensorNetwork is an open source library for implementing tensor network algorithms in TensorFlow. We describe a tree tensor network (TTN) algorithm for approximating the ground state of either a periodic quantum spin chain (1D) or a lattice model on a thin torus (2D), and implement the algorithm using TensorNetwork. We use a standard energy minimization procedure over a TTN ansatz with bond dimension $\chi$, with a computational cost that scales as $O(\chi^4)$. Using bond dimension $\chi \in [32,256]$ we compare the use of CPUs with GPUs and observe significant computational speed-ups, up to a factor of $100$, using a GPU and the TensorNetwork library.

Authors

J. Hidary

3 papers

A. Milsted

2 papers

M. Ganahl

2 papers

TL;DR

Abstract

Authors

References42 items

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