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arXiv:0911.0201 · IEEE Conference on Computational Complexity (CCC)

No Strong Parallel Repetition with Entangled and Non-signaling Provers

Julia Kempe, Oded Regev

Published Jun 1, 2010• 33 citations
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Abstract

We consider one-round games between a classical verifier and two provers. One of the main questions in this area is the parallel repetition question: If the game is played H times in parallel, does the maximum winning probability decay exponentially in ℓ? In the classical setting, this question was answered in the affirmative by Raz. More recently the question arose whether the decay is of the form (1 - ⊖ (ε))ℓwhere 1 - ε is the value of the game and H is the number of repetitions. This question is known as the strong parallel repetition question and was motivated by its connections to the unique games conjecture. It was resolved by Raz who showed that strong parallel repetition does not hold, even in the very special case of games known as XOR games. This opens the question whether strong parallel repetition holds in the case when the provers share entanglement. Evidence for this is provided by the behavior of XOR games, which have strong (in fact perfect) parallel repetition, and by the recently proved strong parallel repetition of linear unique games. A similar question was open for games with so-called non-signaling provers. Here the best known parallel repetition theorem is due to Holenstein, and is of the form (1 - ⊖ (ε2))ℓ. We show that strong parallel repetition holds neither with entangled provers nor with non-signaling provers. In particular we obtain that Holenstein's bound is tight. Along the way we also provide a tight characterization of the asymptotic behavior of the entangled value under parallel repetition of unique games in terms of a semidefinite program.

DOI
10.1109/ccc.2010.10

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The parallel repetition theorem states that, for any two-prover game with value $1-\epsilon$ (for, say, $\epsilon\leq1/2$), the value of the game repeated in parallel n times is at most $(1-\epsilon^c)^{\Omega(n/s)}$, where s is the answer's length (of the original game) and c is a universal constant [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803]. Several researchers asked whether this bound could be improved to $(1-\epsilon)^{\Omega(n/s)}$; this question is usually referred to as the strong parallel repetition problem. We show that the answer to this question is negative. More precisely, we consider the odd cycle game of size m, a two-prover game with value $1-1/2m$. We show that the value of the odd cycle game repeated in parallel n times is at least $1-(1/m)\cdot O(\sqrt{n})$. This implies that, for large enough n (say, $n\geq\Omega(m^2)$), the value of the odd cycle game repeated in parallel n times is at least $(1-1/4m^2)^{O(n)}$. Thus the following hold. 1. For parallel repetition of general games, the bounds of $(1-\epsilon^c)^{\Omega(n/s)}$ given in [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803; T. Holenstein, in Proceedings of STOC 2002, ACM, New York, 2002, pp. 767–775] are of the right form, up to determining the exact value of the constant $c\geq2$. 2. For parallel repetition of XOR games, unique games, and projection games, the bounds of $(1-\epsilon^2)^{\Omega(n)}$ given in [U. Feige, G. Kindler, and R. O'Donnell, in Proceedings of CCC 2007, IEEE Computer Society, Washington, DC, 2007, pp. 179–192] (for XOR games) and in [A. Rao, in Proceedings of STOC 2008, ACM, New York, 2008, pp. 1–10] (for unique and projection games) are tight. 3. For parallel repetition of the odd cycle game, the bound of $1-(1/m)\cdot\tilde{\Omega}(\sqrt{n})$ given in [U. Feige, G. Kindler, and R. O'Donnell, in Proceedings of CCC 2007, IEEE Computer Society, Washington, DC, 2007, pp. 179–192] is almost tight. A major motivation for the recent interest in the strong parallel repetition problem is that a strong parallel repetition theorem would have implied that the unique game conjecture is equivalent to the NP hardness of distinguishing between instances of Max-Cut that are at least $1-\epsilon^2$ satisfiable from instances that are at most $1-(2/\pi)\cdot\epsilon$ satisfiable. Our results suggest that this cannot be proved just by improving the known bounds on parallel repetition.

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We show a connection between the semidefinite relaxation of unique games and their behavior under parallel repetition. Specifically,denoting by val(G) the value of a two-prover unique game G, andby sdpval(G) the value of a natural semidefinite program to approximate val(G), we prove that for every l epsi N, if sdpval(G) ges 1-delta, then val(Gl) ges 1-radicsldelta. Here, Gldenotes the l-fold parallel repetition of G, and s=O(log(k/delta)), where k denotes the alphabet size of the game. For the special case where G is an XOR game (i.e., k=2), we obtain the same bound but with s as an absolute constant. Our bounds on s are optimal up to a factor of O(log(1/delta)). For games with a significant gap between the quantities val(G) and sdpval(G), our result implies that val(Gl) may be much larger than val(G)l, giving a counterexample to the strong parallel repetition conjecture. In a recent breakthrough, Raz (FOCS'08) has shown such an example using the max-cut game on oddcycles. Our results are based on a generalization of his techniques.

Annual Symposium on Foundations of Computer Science•Oct 1, 2008•46 citations
We consider one-round games between a classical verifier and two provers. One of the main questions in this area is the parallel repetition question: If the game is played H times in parallel, does the maximum winning probability decay exponentially in ℓ? In the classical setting, this question was answered in the affirmative by Raz. More recently the question arose whether the decay is of the form (1 - ⊖ (ε))ℓwhere 1 - ε is the value of the game and H is the number of repetitions. This question is known as the strong parallel repetition question and was motivated by its connections to the unique games conjecture. It was resolved by Raz who showed that strong parallel repetition does not hold, even in the very special case of games known as XOR games. This opens the question whether strong parallel repetition holds in the case when the provers share entanglement. Evidence for this is provided by the behavior of XOR games, which have strong (in fact perfect) parallel repetition, and by the recently proved strong parallel repetition of linear unique games. A similar question was open for games with so-called non-signaling provers. Here the best known parallel repetition theorem is due to Holenstein, and is of the form (1 - ⊖ (ε2))ℓ. We show that strong parallel repetition holds neither with entangled provers nor with non-signaling provers. In particular we obtain that Holenstein's bound is tight. Along the way we also provide a tight characterization of the asymptotic behavior of the entangled value under parallel repetition of unique games in terms of a semidefinite program.
We consider a class of two-prover interactive proof systems where each prover returns a single bit to the verifier and the verifier's verdict is a function of the XOR of the two bits received. We show that, when the provers are allowed to coordinate their behavior using a shared entangled quantum state, a perfect parallel repetition theorem holds in the following sense. The prover's optimal success probability for simultaneously playing a collection of XOR proof systems is exactly the product of the individual optimal success probabilities. This property is remarkable in view of the fact that, in the classical case (where the provers can only utilize classical information), it does not hold. The theorem is proved by analyzing parities of XOR proof systems using semidefinite programming techniques, which we then relate to parallel repetitions of XOR games via Fourier analysis.
We study the behavior of the entangled value of two-player one-round projection games under parallel repetition. We show that for any projection game G of entangled value 1 - εc)k), for some universal constant c ≥ 1. Previously parallel repetition with an exponential decay in k was only known for the case of XOR and unique games. To prove the theorem we extend an analytical framework recently introduced by Dinur and Steurer for the study of the classical value of projection games under parallel repetition. Our proof, as theirs, relies on the introduction of a simple relaxation of the entangled value that is perfectly multiplicative. The main technical component of the proof consists in showing that the relaxed value remains tightly connected to the entangled value, thereby establishing the parallel repetition theorem. More generally, we obtain results on the behavior of the entangled value under products of arbitrary (not necessarily identical) projection games. Relating our relaxed value to the entangled value is done by giving an algorithm for converting a relaxed variant of quantum strategies that we call “vector quantum strategy” to a quantum strategy. The algorithm is considerably simpler in case the bipartite distribution of questions in the game has good expansion properties. When this is not the case, rounding relies on a quantum analogue of Holenstein's correlated sampling lemma which may be of independent interest. Our “quantum correlated sampling lemma” generalizes results of van Dam and Hayden on universal embezzlement to the following approximate scenario: two isolated parties, given classical descriptions of arbitrary bipartite states |ψ〉, |φ〉 respectively such that |ψ〉 ≈ |φ〉, are able to locally generate a joint entangled state|Ψ〉 ≈ |ψ〉 ≈ |φ〉 using an initial entangled state that is independent of their inputs.
We consider one-round games between a classical referee and two players. One of the main questions in this area is the parallel repetition question: Is there a way to decrease the maximum winning probability of a game without increasing the number of rounds or the number of players? Classically, efforts to resolve this question, open for many years, have culminated in Raz's celebrated parallel repetition theorem on one hand, and in efficient product testers for PCPs on the other. In the case where players share entanglement, the only previously known results are for special cases of games, and are based on techniques that seem inherently limited. Here we show for the first time that the maximum success probability of entangled games can be reduced through parallel repetition, provided it was not initially 1. Our proof is inspired by a seminal result of Feige and Kilian in the context of classical two-prover one-round interactive proofs. One of the main components in our proof is an orthogonalization lemma for operators, which might be of independent interest.
We consider a class of two-prover interactive proof systems where each prover returns a single bit to the verifier and the verifier's verdict is a function of the XOR of the two bits received. We show that, when the provers are allowed to coordinate their behavior using a shared entangled quantum state, a perfect parallel repetition theorem holds in the following sense. The prover's optimal success probability for simultaneously playing a collection of XOR proof systems is exactly the product of the individual optimal success probabilities. This property is remarkable in view of the fact that, in the classical case (where the provers can only utilize classical information), it does not hold. The theorem is proved by analyzing parities of XOR proof systems using semidefinite programming techniques, which we then relate to parallel repetitions of XOR games via Fourier analysis.
The parallel repetition theorem states that, for any two-prover game with value 1−ϵ1-\epsilon1−ϵ (for, say, ϵ≤1/2\epsilon\leq1/2ϵ≤1/2), the value of the game repeated in parallel n times is at most (1−ϵc)Ω(n/s)(1-\epsilon^c)^{\Omega(n/s)}(1−ϵc)Ω(n/s), where s is the answer's length (of the original game) and c is a universal constant [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803]. Several researchers asked whether this bound could be improved to (1−ϵ)Ω(n/s)(1-\epsilon)^{\Omega(n/s)}(1−ϵ)Ω(n/s); this question is usually referred to as the strong parallel repetition problem. We show that the answer to this question is negative. More precisely, we consider the odd cycle game of size m, a two-prover game with value 1−1/2m1-1/2m1−1/2m. We show that the value of the odd cycle game repeated in parallel n times is at least 1−(1/m)⋅O(n)1-(1/m)\cdot O(\sqrt{n})1−(1/m)⋅O(n​). This implies that, for large enough n (say, n≥Ω(m2)n\geq\Omega(m^2)n≥Ω(m2)), the value of the odd cycle game repeated in parallel n times is at least (1−1/4m2)O(n)(1-1/4m^2)^{O(n)}(1−1/4m2)O(n). Thus the following hold. 1. For parallel repetition of general games, the bounds of (1−ϵc)Ω(n/s)(1-\epsilon^c)^{\Omega(n/s)}(1−ϵc)Ω(n/s) given in [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803; T. Holenstein, in Proceedings of STOC 2002, ACM, New York, 2002, pp. 767–775] are of the right form, up to determining the exact value of the constant c≥2c\geq2c≥2. 2. For parallel repetition of XOR games, unique games, and projection games, the bounds of (1−ϵ2)Ω(n)(1-\epsilon^2)^{\Omega(n)}(1−ϵ2)Ω(n) given in [U. Feige, G. Kindler, and R. O'Donnell, in Proceedings of CCC 2007, IEEE Computer Society, Washington, DC, 2007, pp. 179–192] (for XOR games) and in [A. Rao, in Proceedings of STOC 2008, ACM, New York, 2008, pp. 1–10] (for unique and projection games) are tight. 3. For parallel repetition of the odd cycle game, the bound of 1−(1/m)⋅Ω~(n)1-(1/m)\cdot\tilde{\Omega}(\sqrt{n})1−(1/m)⋅Ω~(n​) given in [U. Feige, G. Kindler, and R. O'Donnell, in Proceedings of CCC 2007, IEEE Computer Society, Washington, DC, 2007, pp. 179–192] is almost tight. A major motivation for the recent interest in the strong parallel repetition problem is that a strong parallel repetition theorem would have implied that the unique game conjecture is equivalent to the NP hardness of distinguishing between instances of Max-Cut that are at least 1−ϵ21-\epsilon^21−ϵ2 satisfiable from instances that are at most 1−(2/π)⋅ϵ1-(2/\pi)\cdot\epsilon1−(2/π)⋅ϵ satisfiable. Our results suggest that this cannot be proved just by improving the known bounds on parallel repetition.
We show a connection between the semidefinite relaxation of unique games and their behavior under parallel repetition. Specifically,denoting by val(G) the value of a two-prover unique game G, andby sdpval(G) the value of a natural semidefinite program to approximate val(G), we prove that for every l epsi N, if sdpval(G) ges 1-delta, then val(Gl) ges 1-radicsldelta. Here, Gldenotes the l-fold parallel repetition of G, and s=O(log(k/delta)), where k denotes the alphabet size of the game. For the special case where G is an XOR game (i.e., k=2), we obtain the same bound but with s as an absolute constant. Our bounds on s are optimal up to a factor of O(log(1/delta)). For games with a significant gap between the quantities val(G) and sdpval(G), our result implies that val(Gl) may be much larger than val(G)l, giving a counterexample to the strong parallel repetition conjecture. In a recent breakthrough, Raz (FOCS'08) has shown such an example using the max-cut game on oddcycles. Our results are based on a generalization of his techniques.