A doubly exponential upper bound on noisy EPR states for binary games
Penghui Yao

TL;DR
This paper establishes a doubly exponential upper bound on the number of noisy EPR states needed for players to approximate the value of binary mono-state entangled games, advancing understanding in quantum complexity and nonlocal games.
Contribution
It introduces a doubly exponential bound for noisy EPR states in mono-state binary games and develops new Fourier analysis techniques on matrix spaces.
Findings
Doubly exponential upper bound on noisy EPR states for game approximation
New Fourier analysis methods on matrix spaces
Progress towards the decidability of MIP* complexity class
Abstract
This paper initiates the study of a class of entangled games, mono-state games, denoted by , where is a two-player one-round game and is a bipartite state independent of the game . In the mono-state game , the players are only allowed to share arbitrary copies of . This paper provides a doubly exponential upper bound on the copies of for the players to approximate the value of the game to an arbitrarily small constant precision for any mono-state binary game , if is a noisy EPR state, which is a two-qubit state with completely mixed states as marginals and maximal correlation less than . In particular, it includes , an EPR state with an arbitrary depolarizing noise .The structure of the proofs is built the recent framework about…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Complexity and Algorithms in Graphs · Computability, Logic, AI Algorithms
