A quantum algorithm for additive approximation of Ising partition functions
Akira Matsuo, Keisuke Fujii, and Nobuyuki Imoto

TL;DR
This paper presents a quantum algorithm for approximating Ising model partition functions on square lattices, demonstrating quantum advantage and extending applicability to physically relevant parameters.
Contribution
It introduces a quantum algorithm for additive approximation of Ising partition functions that works on real parameters and improves approximation scale exponentially over classical methods.
Findings
The algorithm solves BQP-complete problems in this domain.
It extends to real physical parameters of Ising models.
Provides evidence against efficient classical multiplicative approximation.
Abstract
We investigate quantum computational complexity of calculating partition functions of Ising models. We construct a quantum algorithm for an additive approximation of Ising partition functions on square lattices. To this end, we utilize the overlap mapping developed by Van den Nest, D\"ur, and Briegel [Phys. Rev. Lett. 98, 117207 (2007)] and its interpretation through measurement-based quantum computation (MBQC). We specify an algorithmic domain, on which the proposed algorithm works, and an approximation scale, which determines the accuracy of the approximation. We show that the proposed algorithm does a nontrivial task, which would be intractable on any classical computer, by showing the problem solvable by the proposed quantum algorithm are BQP-complete. In the construction of the BQP-complete problem coupling strengths and magnetic fields take complex values. However, the Ising…
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