The task of manipulating correlated random variables in a distributed setting has received attention in the fields of both Information Theory and Computer Science. Often shared correlations can be converted, using a little amount of communication, into perfectly shared uniform random variables. Such perfect shared randomness, in turn, enables the solutions of many tasks. Even the reverse conversion of perfectly shared uniform randomness into variables with a desired form of correlation turns out to be insightful and technically useful. In this article, we describe progress-to-date on such problems and lay out pertinent measures, achievability results, limits of performance, and point to new directions.

中文翻译：

---

产生相关性的交流：统一调查

在分布式环境中操纵相关随机变量的任务在信息论和计算机科学领域都受到关注。通常共享的相关性可以通过少量的交流转换为完全共享的统一随机变量。这种完美的共享随机性反过来又使许多任务的解决方案成为可能。即使将完全共享的均匀随机性反向转换为具有所需相关性形式的变量，也证明是有见地和技术上有用的。在本文中，我们描述了此类问题的最新进展，并列出了相关措施、可实现性结果、性能限制，并指出了新的方向。