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Main Authors: Carlson, Charlie, Jorquera, Zackary, Kolla, Alexandra, Kordonowy, Steven, Wayland, Stuart
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2309.10957
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author Carlson, Charlie
Jorquera, Zackary
Kolla, Alexandra
Kordonowy, Steven
Wayland, Stuart
author_facet Carlson, Charlie
Jorquera, Zackary
Kolla, Alexandra
Kordonowy, Steven
Wayland, Stuart
contents We initiate the algorithmic study of the Quantum Max-$d$-Cut problem, a quantum generalization of the well-known Max-$d$-Cut problem. The Quantum Max-$d$-Cut problem involves finding a quantum state that maximizes the expected energy associated with the projector onto the antisymmetric subspace of two, $d$-dimensional qudits over all local interactions. Equivalently, this problem is physically motivated by the $SU(d)$-Heisenberg model, a spin glass model that generalized the well-known Heisenberg model over qudits. We develop a polynomial-time randomized approximation algorithm that finds product-state solutions of mixed states with bounded purity that achieve non-trivial performance guarantees. Moreover, we prove the tightness of our analysis by presenting an algorithmic gap instance for Quantum Max-d-Cut problem with $d \geq 3$.
format Preprint
id arxiv_https___arxiv_org_abs_2309_10957
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Approximation Algorithms for Quantum Max-$d$-Cut
Carlson, Charlie
Jorquera, Zackary
Kolla, Alexandra
Kordonowy, Steven
Wayland, Stuart
Quantum Physics
We initiate the algorithmic study of the Quantum Max-$d$-Cut problem, a quantum generalization of the well-known Max-$d$-Cut problem. The Quantum Max-$d$-Cut problem involves finding a quantum state that maximizes the expected energy associated with the projector onto the antisymmetric subspace of two, $d$-dimensional qudits over all local interactions. Equivalently, this problem is physically motivated by the $SU(d)$-Heisenberg model, a spin glass model that generalized the well-known Heisenberg model over qudits. We develop a polynomial-time randomized approximation algorithm that finds product-state solutions of mixed states with bounded purity that achieve non-trivial performance guarantees. Moreover, we prove the tightness of our analysis by presenting an algorithmic gap instance for Quantum Max-d-Cut problem with $d \geq 3$.
title Approximation Algorithms for Quantum Max-$d$-Cut
topic Quantum Physics
url https://arxiv.org/abs/2309.10957