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P2 Spectral and combinatorial methods for efficiently computing the rank of unambiguous finite automata

高效计算无歧义有限自动机秩的谱方法与组合方法
LMCS vol.Volume 22, Issue 32026匹配度 2/10 · 该论文研究无歧义有限自动机与零一矩阵幺半群的最小秩计算,属于自动机理论/计算复杂性方向,与用户关注的静态分析、LLM/Agent、浮点程序分析和贝叶斯程序分析均无直接交集。虽然形式化方法背景略有相关,但研究问题和应用场景距离用户画像较远。引用 0 inbox
Stefan Kiefer, Andrew Ryzhikov
crossref: 2026-10-02

AI 速览

一句话:证明计算无歧义有限自动机对应零一矩阵幺半群最小秩属于 NC,并给出 O(mn^4) 时间算法及弱 Černý 型结果。

论文研究由零一矩阵生成的幺半群,其生成集可视为无歧义有限自动机(UFA)的矩阵表示,目标是计算该幺半群中矩阵的最小秩。作者运用线性代数/谱技术与组合方法,证明该问题属于 NC,并可达到 O(mn^4) 时间和 O(n^2) 空间;另给出组合算法,时间 O(mn^4)、空间 O(n^3)。副产品是一个弱化的 Černý 猜想推广:总存在规模 O(n^2) 的直线程序描述达到最小秩的乘积。对全 DFA 特例,最小秩对应状态集在字作用下最小像的大小,组合算法时间为 O(n^3+mn^2)。

问题
如何高效计算由 n×n 零一矩阵生成的幺半群中的最小秩,该问题等价于无歧义有限自动机矩阵表示中的最小秩计算。
方法
使用线性代数/谱方法证明复杂度上界,并设计组合算法;还构造直线程序来描述达到最小秩的矩阵乘积。
评估
通过理论复杂度分析证明问题在 NC 中,给出 O(mn^4) 时间与 O(n^2)/O(n^3) 空间算法,并对 total DFA 特例给出 O(n^3+mn^2) 时间算法。
原文摘要(Abstract)

A zero-one matrix is a matrix with entries from $\{0, 1\}$. We study monoids containing only such matrices. A finite set of zero-one matrices generating such a monoid can be seen as the matrix representation of an unambiguous finite automaton, an important generalisation of deterministic finite automata which shares many of their good properties. Let $\mathcal{A}$ be a finite set of $n \times n$ zero-one matrices generating a monoid of zero-one matrices, and $m$ be the cardinality of $\mathcal{A}$. We study the computational complexity of computing the minimum rank of a matrix in the monoid generated by $\mathcal{A}$. By using linear-algebraic techniques, we show that this problem is in $\textsf{NC}$ and can be solved in $\mathcal{O}(mn^4)$ time and $\mathcal{O}(n^2)$ space. We also provide a combinatorial algorithm finding a matrix of minimum rank in $\mathcal{O}(mn^4)$ time and $\mathcal{O}(n^3)$ space. As a byproduct, we show a very weak version of a generalisation of the Černý conjecture: there always exists a straight line program of size $\mathcal{O}(n^2)$ describing a product resulting in a matrix of minimum rank. For the special case corresponding to total DFAs (that is, for the case where all matrices have exactly one 1 in each row), the minimum rank is the size of the smallest image of the set of all states under the action of a word. Our combinatorial algorithm finds a matrix of minimum rank in time $\mathcal{O}(n^3 + mn^2)$ in this case.

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BibTeX
@article{paperbot12170,
  title = {Spectral and combinatorial methods for efficiently computing the rank of unambiguous finite automata},
  author = {Stefan Kiefer and Andrew Ryzhikov},
  journal = {Logical Methods in Computer Science},
  volume = {Volume 22, Issue 3},
  year = {2026},
  doi = {10.46298/lmcs-22(3:10)2026}
}