The Computational Advantage of MIP* Vanishes in the Presence of Noise

The class MIP* of quantum multiprover interactive proof systems with entanglement is much more powerful than its classical counterpart MIP [ 8 , 31 , 32 ]: while MIP = NEXP, the quantum class MIP * is equal to RE, a class including the halting problem. This is because the provers in MIP * can share unbounded quantum entanglement. However, recent works [ 53 , 54 ] have shown that this advantage is significantly reduced if the provers’ shared state contains noise. This article attempts to exactly characterize the effect of noise on the computational power of quantum multiprover interactive proof systems. We investigate the quantum two-prover one-round interactive system MIP * [poly, O (1)], where the verifier sends polynomially many bits to the provers and the provers send back constantly many bits. We show that noise completely destroys the computational advantage given by shared entanglement in this model. Specifically, we show that if the provers are allowed to share arbitrarily many EPR states, where each EPR state is affected by an arbitrarily small constant amount of noise, the resulting complexity class is equivalent to NEXP = MIP. This improves significantly on the previous best-known bound of NEEEXP (nondeterministic triply exponential time) [ 53 ]. We also show that this collapse in power is due to noise, rather than the O (1) answer size, by showing that allowing for noiseless EPR states gives the class the full power of RE = MIP * [poly, poly]. Along the way, we develop two technical tools of independent interest. First, we give a new, deterministic tester for the positivity of an exponentially large matrix, provided that it has a low-degree Fourier decomposition in terms of Pauli matrices. Secondly, we develop a new invariance principle for smooth matrix functions having bounded third-order Fréchet derivatives or which are Lipschitz continuous.