Dubova and Yang prove quantum diffusion and bulk eigenvector delocalization for 1D Gaussian random band matrices with width W ≫ N^{8/11}, improving on the earlier W ≫ N^{3/4}.
Extracting the Unknown from Long Math Problems
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In problem solving, understanding the problem that one seeks to solve is an essential initial step. In this paper, we propose computational methods for facilitating problem understanding through the task of recognizing the unknown in specifications of long Math problems. We focus on the topic of Probability. Our experimental results show that learning models yield strong results on the task, a promising first step towards human interpretable, modular approaches to understanding long Math problems.
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Quantum diffusion and delocalization in one-dimensional band matrices via the flow method
Dubova and Yang prove quantum diffusion and bulk eigenvector delocalization for 1D Gaussian random band matrices with width W ≫ N^{8/11}, improving on the earlier W ≫ N^{3/4}.