Approximate Contraction of Arbitrary Tensor Networks with a Flexible and Efficient Density Matrix Algorithm

Tensor network contractions are widely used in statistical physics, quantum computing, and computer science. We introduce a method to efficiently approximate tensor network contractions using low-rank approximations, where each intermediate tensor generated during the contractions is approximated as...

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Bibliographic Details
Main Authors: Linjian Ma, Matthew Fishman, Edwin Miles Stoudenmire, Edgar Solomonik
Format: Article
Language:English
Published: Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften 2024-12-01
Series:Quantum
Online Access:https://quantum-journal.org/papers/q-2024-12-27-1580/pdf/