Approximating Random Walks in $\widetilde{O}(\log n + \log^2 κ)$ Space for $κ$-Conditioned Graphs

For $κ>1$, a directed graph is $κ$-conditioned if it is $κ$-mixing and its stationary distribution is approximated by the uniform distribution within a factor of $κ$. We present a deterministic algorithm that approximates the stationary distribution of a $κ$-conditioned graph to inverse polynomial relative error in $O((\log n + \log^2 κ) \log \log n)$ space. In the regime $κ= \exp(Θ(\log^αn))$ for any $α\in (0, 2/3)$, our result improves the best-known $O(\log n \sqrt{\log κ} / \sqrt{\log \log n})$ space bound for approximating $κ$-step random walks in general directed graphs by [Hoza, RANDOM 2021]. We release this preliminary version due to recent rumors of LLM-based progress on related problems and uncertainty about when those results may appear. Further implementation details will be provided in a subsequent version.