Conference item
Efficiently computing the minimum rank of a matrix in a monoid of zero-one matrices
- Abstract:
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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 A be a finite set of n × n zero-one matrices generating a monoid of zero-one matrices, and m be the cardinality of A. We study the computational complexity of computing the minimum rank of a matrix in the monoid generated by A. By using linear-algebraic techniques, we show that this problem is in NC and can be solved in O(mn4) time. We also provide a combinatorial algorithm finding a matrix of minimum rank in O(n2+ω + mn4) time, where 2 ≤ ω ≤ 2.4 is the matrix multiplication exponent. 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 O(n2) describing a product resulting in a matrix of minimum rank.
For the special case corresponding to complete 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 states under the action of a word. Our combinatorial algorithm finds a matrix of minimum rank in time O(n3 + mn2) in this case.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 883.8KB, Terms of use)
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- Publisher copy:
- 10.4230/LIPIcs.STACS.2025.61
Authors
- Publisher:
- Schloss Dagstuhl
- Host title:
- 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025)
- Pages:
- 61:1-61:22
- Series:
- Leibniz International Proceedings in Informatics (LIPIcs)
- Series number:
- 327
- Publication date:
- 2025-02-24
- Acceptance date:
- 2025-02-11
- Event title:
- 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025)
- DOI:
- ISSN:
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1868-8969
- ISBN:
- 9783959773652
- Language:
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English
- Keywords:
- Pubs id:
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2095226
- Local pid:
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pubs:2095226
- Deposit date:
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2025-04-07
- ARK identifier:
Terms of use
- Copyright holder:
- Kiefer and Ryzhikov
- Copyright date:
- 2025
- Rights statement:
- © Stefan Kiefer and Andrew Ryzhikov; licensed under Creative Commons License CC-BY 4.0.
- Licence:
- CC Attribution (CC BY)
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