Given an $n\times n$ matrix with integer entries in the range $[-h,h]$, how close can two of its distinct eigenvalues be? The best previously known examples have a minimum gap of $h^{-O(n)}$. Here we give an explicit construction of matrices with entries in $[0,h]$ with two eigenvalues separated by at most $h^{-n^2/16+o(n^2)}$. Up to a constant in the exponent, this agrees with the known lower bound of $\Omega((2\sqrt{n})^{-n^2}h^{-n^2})$ \cite{mahler1964inequality}. Bounds on the minimum gap are relevant to the worst case analysis of algorithms for diagonalization and computing canonical forms of integer matrices (e.g. \cite{dey2021bit}). In addition to our explicit construction, we show there are many matrices with a slightly larger gap of roughly $h^{-n^2/32}$. We also construct 0-1 matrices which have two eigenvalues separated by at most $2^{-n^2/64+o(n^2)}$.
翻译:根据$n_times nn_times nn_trom, 内有在 $-h, h) 范围内的整数条目, 其两个不同的电子值的距离会有多大? 最先知道的范例至少有$@- O(n) $。 这里我们给出一个明确的矩阵结构, 以$[0, h] $为条目, 以两个电子值最多以$h ⁇ - n%2/16+o(n) $2美元分隔。 直至一个常数, 这与已知的较低约束值 $( 2\\ qrt{n} } ⁇ _ __n} { __\\\\ n% 2} 的差数相同 。 在最小差距上找到的矩阵, $[ $[ mahler]- main2} 。 最小值与最差的算法分析有关, 用于分解和计算整数矩阵形式( 例如\ cite{dey{dey2021bit} 。 除了我们明确的构造之外, 我们还显示有许多矩阵, 略为大约为 $__n________xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx