$E_γ$-Resolvability

The conventional channel resolvability refers to the minimum rate needed for an input process to approximate the channel output distribution in total variation distance. In this paper we study $E{\gamma}$-resolvability, in which total variation is replaced by the more general $E{\gamma}$ distance. A general one-shot achievability bound for the precision of such an approximation is developed. Let $Q{\sf X|U}$ be a random transformation, $n$ be an integer, and $E\in(0,+\infty)$. We show that in the asymptotic setting where $\gamma=\exp(nE)$, a (nonnegative) randomness rate above $\inf{Q{\sf U}: D(Q{\sf X}|{{\pi}}{\sf X})\le E} {D(Q{\sf X}|{{\pi}}{\sf X})+I(Q{\sf U},Q{\sf X|U})-E}$ is sufficient to approximate the output distribution ${{\pi}}{\sf X}^{\otimes n}$ using the channel $Q{\sf X|U}^{\otimes n}$, where $Q{\sf U}\to Q{\sf X|U}\to Q{\sf X}$, and is also necessary in the case of finite $\mathcal{U}$ and $\mathcal{X}$. In particular, a randomness rate of $\inf{Q{\sf U}}I(Q{\sf U},Q{\sf X|U})-E$ is always sufficient. We also study the convergence of the approximation error under the high probability criteria in the case of random codebooks. Moreover, by developing simple bounds relating $E_{\gamma}$ and other distance measures, we are able to determine the exact linear growth rate of the approximation errors measured in relative entropy and smooth R\'{e}nyi divergences for a fixed-input randomness rate. The new resolvability result is then used to derive 1) a one-shot upper bound on the probability of excess distortion in lossy compression, which is exponentially tight in the i.i.d.~setting, 2) a one-shot version of the mutual covering lemma, and 3) a lower bound on the size of the eavesdropper list to include the actual message and a lower bound on the eavesdropper false-alarm probability in the wiretap channel problem, which is (asymptotically) ensemble-tight.