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arXiv:1411.1582

Non-signalling parallel repetition using de Finetti reductions

Rotem Arnon-Friedman, Renato Renner, Thomas Vidick

Published Nov 6, 2014• 6 citations
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Abstract

In the context of multiplayer games, the parallel repetition problem can be phrased as follows: given a game $G$ with optimal winning probability $1-α$ and its repeated version $G^n$ (in which $n$ games are played together, in parallel), can the players use strategies that are substantially better than ones in which each game is played independently? This question is relevant in physics for the study of correlations and plays an important role in computer science in the context of complexity and cryptography. In this work the case of multiplayer non-signalling games is considered, i.e., the only restriction on the players is that they are not allowed to communicate during the game. For complete-support games (games where all possible combinations of questions have non-zero probability to be asked) with any number of players we prove a threshold theorem stating that the probability that non-signalling players win more than a fraction $1-α+β$ of the $n$ games is exponentially small in $nβ^2$, for every $0\leq β\leq α$. For games with incomplete support we derive a similar statement, for a slightly modified form of repetition. The result is proved using a new technique, based on a recent de Finetti theorem, which allows us to avoid central technical difficulties that arise in standard proofs of parallel repetition theorems.

DOI
10.48550/arxiv.1411.1582

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In the context of multiplayer games, the parallel repetition problem can be phrased as follows: given a game GGG with optimal winning probability 1−α1-α1−α and its repeated version GnG^nGn (in which nnn games are played together, in parallel), can the players use strategies that are substantially better than ones in which each game is played independently? This question is relevant in physics for the study of correlations and plays an important role in computer science in the context of complexity and cryptography. In this work the case of multiplayer non-signalling games is considered, i.e., the only restriction on the players is that they are not allowed to communicate during the game. For complete-support games (games where all possible combinations of questions have non-zero probability to be asked) with any number of players we prove a threshold theorem stating that the probability that non-signalling players win more than a fraction 1−α+β1-α+β1−α+β of the nnn games is exponentially small in nβ2nβ^2nβ2, for every 0≤β≤α0\leq β\leq α0≤β≤α. For games with incomplete support we derive a similar statement, for a slightly modified form of repetition. The result is proved using a new technique, based on a recent de Finetti theorem, which allows us to avoid central technical difficulties that arise in standard proofs of parallel repetition theorems.
In the context of multiplayer games, the parallel repetition problem can be phrased as follows: given a game G with optimal winning probability 1 - α and its repeated version Gn(in which n games are played together, in parallel), can the players use strategies that are substantially better than ones in which each game is played independently? This question is relevant in physics for the study of correlations and plays an important role in computer science in the context of complexity and cryptography. In this paper, the case of multiplayer non-signaling games is considered, i.e., the only restriction on the players is that they are not allowed to communicate during the game. For complete-support games (games where all possible combinations of questions have non-zero probability to be asked) with any number of players, we prove a threshold theorem stating that the probability that non-signaling players win more than a fraction 1-α+β of the n games is exponentially small in nβ2for every 0 ≤ β ≤ α. For games with incomplete support, we derive a similar statement for a slightly modified form of repetition. The result is proved using a new technique based on a recent de Finetti theorem, which allows us to avoid central technical difficulties that arise in standard proofs of parallel repetition theorems.
We use a recently discovered constrained de Finetti reduction (aka "Post-Selection Lemma") to study the parallel repetition of multi-player non-local games under no-signalling strategies.Since the technique allows us to reduce general strategies to independent plays, we obtain parallel repetition (corresponding to winning all rounds) in the same way as exponential concentration of the probability to win a fraction larger than the value of the game.Our proof technique leads us naturally to a relaxation of no-signalling (NS) strategies, which we dub sub-no-signalling (SNOS).While for two players the two concepts coincide, they differ for three or more players.Our results are most complete and satisfying for arbitrary number of sub-no-signalling players, where we get universal parallel repetition and concentration for any game, while the no-signalling case is obtained as a corollary, but only for games with "full support".
We consider the natural extension of two-player nonlocal games to an arbitrary number of players. An important question for such nonlocal games is their behavior under parallel repetition. For two-player nonlocal games, it is known that both the classical and the non-signaling value of any game converges to zero exponentially fast under parallel repetition, given that the game is non-trivial to start with (i.e., has classical/non-signaling value <1). Very recent results show similar behavior for the quantum value of a two-player game under parallel repetition. For nonlocal games with three or more players, very little is known up to present on their behavior under parallel repetition; this is true for the classical, the quantum and the non-signaling value. In this work, we show a parallel repetition theorem for the non-signaling value of a large class of multi-player games, for an arbitrary number of players. Our result applies to all multi-player games for which all possible combinations of questions have positive probability; this class in particular includes all free games, in which the questions to the players are chosen independently. Specifically, we prove that if the original game has a non-signaling value smaller than 1, then the non-signaling value of the nnn-fold parallel repetition is exponentially small in nnn. Our parallel repetition theorem for multi-player games is weaker than the known parallel repetition results for two-player games in that the rate at which the non-signaling value of the game decreases not only depends on the non-signaling value of the original game (and the number of possible responses), but on the complete description of the game. Nevertheless, we feel that our result is a first step towards a better understanding of the parallel repetition of nonlocal games with more than two players.
A two-player game is played by cooperating players who are not allowed to communicate. A referee asks the players questions sampled from some known distribution and decides whether they win or not based on a known predicate of the questions and the players' answers. The parallel repetition of the game is the game in which the referee samples n independent pairs of questions and sends the corresponding questions to the players simultaneously. If the players cannot win the original game with probability better than (1−ϵ)(1-\epsilon)(1−ϵ), what's the best they can do in the repeated game? We improve earlier results of [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803] and [T. Holenstein, Theory Comput., 5 (2009), pp. 141–172], who showed that the players cannot win all copies in the repeated game with probability better than (1−ϵ/2)Ω(nϵ2/c)(1-\epsilon/2)^{\Omega(n\epsilon^2/c)}(1−ϵ/2)Ω(nϵ2/c) (here c is the length of the answers in the game), in the following ways: (i) We show that the probability of winning all copies is (1−ϵ/2)Ω(ϵn)(1-\epsilon/2)^{\Omega(\epsilon n)}(1−ϵ/2)Ω(ϵn) as long as the game is a “projection game,” the type of game most commonly used in hardness of approximation results. (ii) We prove a concentration bound for parallel repetition (of general games) showing that for any constant 0<δ<ϵ0<\delta <\epsilon0<δ<ϵ, the probability that the players win a (1−ϵ+δ)(1-\epsilon+\delta)(1−ϵ+δ) fraction of the games in the parallel repetition is at most exp⁡(−Ωϵ(δ3n/c))\exp\left(-\Omega_{\epsilon}(\delta^3 n/c)\right)exp(−Ωϵ​(δ3n/c)) (here the constant may depend on ϵ\epsilonϵ); our result has applications to testing Bell inequalities, since it implies that the parallel repetition of the CHSH game can be used to get an experiment that has a very large classical versus quantum gap. Our first bound is independent of the answer length and has a better dependence on ϵ\epsilonϵ. By the recent work of Raz [Proceedings of the 494949th Annual IEEE Symposium on Foundations of Computer Science, 2008, pp. 369–373], this bound is tight. Our bound gives a generic way to improve the soundness of a probabilistically checkable proof (PCP), in a way that is independent of the answer length of the PCP. Using it, for every k, one can convert any q query PCP with answer length c, size scscsc, and soundness (1−ϵ)(1-\epsilon)(1−ϵ) into a two-query PCP with answer length ckckck, size O(ck(2s)k)O(ck (2s)^k)O(ck(2s)k), and soundness (1−ϵ/2q)Ω(ϵk/q)(1-\epsilon/2q)^{\Omega(\epsilon k/q)}(1−ϵ/2q)Ω(ϵk/q). Another consequence of our bound is that the unique games conjecture of Khot [Proceedings of the 343434th Annual ACM Symposium on Theory of Computing, 2002, pp. 767–775] can now be shown to be equivalent to the following a priori weaker conjecture: There is an unbounded increasing function f:R+→R+f:\mathbb{R}^+\rightarrow \mathbb{R}^+f:R+→R+ such that for every ϵ>0\epsilon> 0ϵ>0, there exists an alphabet size M(ϵ)M(\epsilon)M(ϵ) for which it is NP-hard to distinguish a unique game with alphabet size M in which a (1−ϵ2)(1-\epsilon^2)(1−ϵ2) fraction of the constraints can be satisfied from one in which a (1−ϵf(1/ϵ))(1-\epsilon f(1/\epsilon))(1−ϵf(1/ϵ)) fraction of the constraints can be satisfied.
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.
This thesis contributes to the study of parallel repetition theorems and concentration bounds for nonlocal games and quantum interactive proofs. We make the following contributions: \n \n- A lemma that is useful for converting parallel repetition theorems (bounds on the probability of winning all instances of a nonlocal game which is being repeated in parallel) into concentration bounds (bounds on winning a certain fraction of the instances). \n \n- Exponentially-decaying concentration bounds for two-player games on the uniform distribution and k-player free games, against quantum strategies. \n \n- A proof that given a quantum interactive proof system with parameters α (the probability with which the verifier can be convinced to accept when they should accept) and β (the soundness error), as long as α > β, both the soundness error and completeness error can be reduced exponentially by repeating the protocol in parallel and requiring an (α + β)/2 fraction of the repetitions to be won. Our result requires a log-factor more repetitions than are necessary in the classical case.