外部信息的新分离结果
New Separations Results for External Information
摘要：
我们得到了布尔函数两方外部信息复杂性的新的分离结果。函数$f(x,y)$的外部信息复杂度是两方协议计算$f$必须向外部观察者揭示的关于输入的最小信息量。我们得到以下结果：1.我们证明了外部和内部信息复杂性之间的指数分离，这是最好的可能，以前没有分离是已知的。2.我们证明了一个近二次分离摊销零错误通信复杂性和外部信息复杂性的总功能，反驳了\cite{Bravermansurvey}的猜想。3.我们证明了一个匹配的上限表明我们的分离结果是紧的。
英文摘要：
We obtain new separation results for the two-party external information complexity of boolean functions. The external information complexity of a function $f(x,y)$ is the minimum amount of information a two-party protocol computing $f$ must reveal to an outside observer about the input. We obtain the following results: 1. We prove an exponential separation between external and internal information complexity, which is the best possible; previously no separation was known. 2. We prove a near-quadratic separation between amortized zero-error communication complexity and external information complexity for total functions, disproving a conjecture of \cite{Bravermansurvey}. 3. We prove a matching upper showing that our separation result is tight.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
