Dynamic normal forms and dynamic characteristic polynomial

Abstract. We present the first fully dynamic algorithm for computing the characteristic polynomial of a matrix. In the generic symmetric case our algorithm supports rank-one updates in O(n2 log n) randomized time and queries in constant time, whereas in the general case the algorithm works in O(n2 k log n) randomized time, where k is the number of invariant factors of the matrix. The algorithm is based on the first dynamic algorithm for computing normal forms of a matrix such as the Frobenius normal form or the tridiagonal symmetric form. The algorithm can be extended to solve the matrix eigenproblem with relative error 2−b in additional O(n log2 n log b) time. Furthermore, it can be used to dynamically maintain the singular value decomposition (SVD) of a generic matrix. Together with the algorithm the hardness of the problem is studied. For the symmetric case we present an Ω(n2 ) lower bound for rank-one updates and an Ω(n) lower bound for element updates.

• Type: Journal
• Year: 2011
• Where: TCS
• Authors: Gudmund Skovbjerg Frandsen, Piotr Sankowski
• Keywords: Algorithm, Dynamic Algorithm, Matrix, TCS 2011, Theoretical Computer Science