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Published March 2016 | Published
Journal Article Open

Non-Signaling Parallel Repetition Using de Finetti Reductions

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 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 nβ^2 for 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.

Additional Information

© 2016 IEEE. IEEE Open Access Publishing Agreement. Manuscript received May 5, 2015; revised September 18, 2015; accepted December 22, 2015. Date of publication January 8, 2016; date of current version February 12, 2016. R. Arnon-Friedman and R. Renner were supported in part by the European Research Council under Grant 258932, in part by the European Commission Strategic Targeted Research Project RAQUEL, in part by the Swiss National Science Foundation via the National Centre of Competence in Research through the QSIT Project, and in part by the CHIST-ERA Project DIQIP. T. Vidick was supported in part by the Simons Institute, Berkeley, CA, USA, in part by the Ministry of Education, Singapore, under the Tier 3 under Grant MOE2012-T3-1-009, and in part by the Perimeter Institute, Waterloo, ON, Canada. The authors would like to thank Anthony Leverrier, Yeong-Cherng Liang, and David Sutter for helpful discussions, and Christian Schaffner for pointing out a mistake in a preliminary version of this work, as well as to the anonymous referees for their helpful comments.

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