On the (im)possibility of non-interactive correlation distillation

  • Authors:
  • Ke Yang

  • Affiliations:
  • 1600 Amphitheatre Parkway, Google Inc., Mountain View, CA 94043, United States

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2007

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Abstract

We study the problem of non-interactive correlation distillation (NICD). Suppose that Alice and Bob each have a string, denoted by A=a0a1…an-1 and B=b0b1…bn-1, respectively. Furthermore, for every k=0,1,…,n-1, (ak,bk) is drawn independently from a distribution , known as the 'noise model'. Alice and Bob wish to 'distill' the correlation non-interactively, i.e., they wish to each apply a function to their strings, and output one random bit, denoted by X and Y, such that Pr[X=Y] can be made as close to 1 as possible. The problem is, for what noise models can they succeed? This problem is related to various topics in computer science, including information reconciliation and random beacons. In fact, if NICD is indeed possible for some general class of noise models, then some of these topics would, in some sense, become straightforward corollaries. We prove two negative results on NICD for various noise models. We prove that, for these models, it is impossible to distill the correlation to be arbitrarily close to 1. We also give an example where Alice and Bob can increase their correlation with one bit of communication (in this case they need to each output two bits). This example, which may be of interest on its own, demonstrates that even the smallest amount of communication is provably more powerful than no communication.