English

On Non-Interactive Simulation of Joint Distributions

Information Theory 2016-04-12 v2 math.IT

Abstract

We consider the following non-interactive simulation problem: Alice and Bob observe sequences XnX^n and YnY^n respectively where {(Xi,Yi)}i=1n\{(X_i, Y_i)\}_{i=1}^n are drawn i.i.d. from P(x,y),P(x,y), and they output UU and VV respectively which is required to have a joint law that is close in total variation to a specified Q(u,v).Q(u,v). It is known that the maximal correlation of UU and VV must necessarily be no bigger than that of XX and YY if this is to be possible. Our main contribution is to bring hypercontractivity to bear as a tool on this problem. In particular, we show that if P(x,y)P(x,y) is the doubly symmetric binary source, then hypercontractivity provides stronger impossibility results than maximal correlation. Finally, we extend these tools to provide impossibility results for the kk-agent version of this problem.

Cite

@article{arxiv.1505.00769,
  title  = {On Non-Interactive Simulation of Joint Distributions},
  author = {Sudeep Kamath and Venkat Anantharam},
  journal= {arXiv preprint arXiv:1505.00769},
  year   = {2016}
}

Comments

25 pages, 13 figures

R2 v1 2026-06-22T09:27:53.167Z