Nonlocal games with noisy maximally entangled states are decidable

TL;DR

This paper demonstrates that for nonlocal games with noisy maximally entangled states, it is possible to approximate the game's value, contrasting with the undecidability results for perfect entangled states.

Contribution

It introduces a new framework for analyzing nonlocal games with noisy entangled states, showing decidability and approximation feasibility where previously undecidable cases existed.

Findings

Upper bounds on the number of copies needed for near-optimal winning probability

Feasibility of approximating game values to arbitrary precision

Development of new quantum Fourier analysis techniques

Abstract

This paper considers a special class of nonlocal games $(G,\psi)$, where $G$ is a two-player one-round game, and $\psi$ is a bipartite state independent of $G$. In the game $(G,\psi)$, the players are allowed to share arbitrarily many copies of $\psi$. The value of the game $(G,\psi)$, denoted by $\omega^*(G,\psi)$, is the supremum of the winning probability that the players can achieve with arbitrarily many copies of preshared states $\psi$. For a noisy maximally entangled state $\psi$, a two-player one-round game $G$ and an arbitrarily small precision $\epsilon>0$, this paper proves an upper bound on the number of copies of $\psi$ for the players to win the game with a probability $\epsilon$ close to $\omega^*(G,\psi)$. Hence, it is feasible to approximately compute $\omega^*(G,\psi)$ to an arbitrarily precision. Recently, a breakthrough result by Ji, Natarajan, Vidick, Wright and Yuen showed that it is undecidable to approximate the values of nonlocal games to a constant precision when the players preshare arbitrarily many copies of perfect maximally entangled states, which implies that $\mathrm{MIP}^*=\mathrm{RE}$. In contrast, our result implies the hardness of approximating nonlocal games collapses when the preshared maximally entangled states are noisy. The paper develops a theory of Fourier analysis on matrix spaces by extending a number of techniques in Boolean analysis and Hermitian analysis to matrix spaces. We establish a series of new techniques, such as a quantum invariance principle and a hypercontractive inequality for random operators, which we believe have further applications.