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(n 2 logn) randomized time and queries in constant time, whereas in the general case the algorithm works in O(n 2 k logn) 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 logb) 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(n 2) lower bound for rank-one updates and an Ω(n) lower bound for element updates.
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References
Giesbrecht, M.: Nearly optimal algorithms for canonical matrix forms. SIAM Journal on Computing 24(5), 948–969 (1995)
Eberly, W.: Asymptotically efficient algorithms for the Frobenius form. Paper 723-26, Department of Computer Science, University of Calgary (2003)
Villard, G.: Computing the Frobenius normal form of a sparse matrix. In: The Third International Workshop on Computer Algebra in Scientific Computing, pp. 395–407. Springer, Heidelberg (2000)
Storjohann, A.: Deterministic computation of the frobenius form. In: FOCS, pp. 368–377 (2001)
Ben-Amram, A., Galil, Z.: On pointers versus addresses. J. Assoc. Comput. Mach. 39, 617–648 (1992)
Pan, V., Chen, Z.: The complexity of the matrix eigenproblem. In: STOC 1999: Proceedings of the thirty-first annual ACM symposium on Theory of computing, pp. 507–516. ACM Press, New York (1999)
Frandsen, G., Hansen, J., Miltersen, P.: Lower bounds for dynamic algebraic problems. Inform. and Comput. 171(2), 333–349 (2001)
Frandsen, P., Frandsen, G.: Dynamic matrix rank. In: Bugliesi, M., Preneel, B., Sassone, V., Wegener, I. (eds.) ICALP 2006. LNCS, vol. 4051, pp. 395–406. Springer, Berlin (2006)
Sankowski, P.: Dynamic Transitive Closure via Dynamic Matrix Inverse. In: FOCS, pp. 509–517 (2004)
Ibarra, O., Moran, S., Rosier, L.: A note on the parallel complexity of computing the rank of order n matrices. Inform. Process. Lett. 11(4-5), 162 (1980)
Mulmuley, K.: A fast parallel algorithm to compute the rank of a matrix over an arbitrary field. In: STOC, pp. 338–339. ACM Press, New York (1986)
Chung, F.R.K.: Spectral Graph Theory. CBMS Regional Conference Series in Mathematics, vol. 92. American Mathematical Society (1997)
Babai, L., Grigoryev, D., Mount, D.: Isomorphism of graphs with bounded eigenvalue multiplicity. In: STOC 1982: Proceedings of the fourteenth annual ACM symposium on Theory of computing, New York, NY, USA, pp. 310–324 (1982)
Fiedler, M.: Algebraic connectivity of graphs. Czechoslovak Mathematical Journal 23(98), 289–305 (1973)
Spielman, D., Teng, S.H.: Spectral partitioning works: Planar graphs and finite element meshes. In: FOCS, pp. 96–105 (1996)
Weiss, Y.: Segmentation using eigenvectors: A unifying view. In: ICCV (2), pp. 975–982 (1999)
Ng, A., Jordan, M., Weiss, Y.: On spectral clustering: Analysis and an algorithm. In: Proceedings of Advances in Neural Information Processing Systems 14 (2001)
Meyer, C.D., J.S.,: Updating finite markov chains by using techniques of group matrix inversion. J. Statist. Comput. Simulat. 11, 163–181 (1980)
Funderlic, R.E., Plemmons, R.J.: Updating lu factorizations for computing stationary distributions. SIAM J. Algebraic Discrete Methods 7(1), 30–42 (1986)
Seneta, E.: Sensivity analysis, ergodicity coefficients, and rank-one updates for finite markov chains. Numerical Solutions of Markov Chains, 121–129 (1991)
Diaconis, P., Stroock, D.: Geometric bounds for eigenvalues of Markov chains. Ann. Appl. Probab. 1(1), 36–61 (1991), http://www.ams.org/mathscinet-getitem?mr=92h:60103
Golub, G.H., Van Loan, C.F.: Matrix computations, 3rd edn. Johns Hopkins Studies in the Mathematical Sciences. Johns Hopkins University Press, Baltimore (1996)
Chandrasekaran, S., Manjunath, B.S., Wang, Y.F., Winkeler, J., Zhang, H.: An eigenspace update algorithm for image analysis. Graph. Models Image Process 59(5), 321–332 (1997)
Kanth, K., Agrawal, D., Singh, A.: Dimensionality reduction for similarity searching in dynamic databases. In: Proceedings of the 1998 ACM SIGMOD international conference on Management of data, NY, USA, pp. 166–176 (1998)
Brand, M.: Fast online svd revisions for lightweight recommender systems. In: Barbará, D., Kamath, C. (eds.) SDM. SIAM, Philadelphia (2003)
Gu, M., Eisenstat, S.C.: A stable and fast algorithm for updating singular value decomposition. Technical Report YALE/DCS/TR-966, Yale University, New Haven, CT (1993)
Gu, M., Eisenstat, S.: Downdating the singular value decomposition. SIAM Journal on Matrix Analysis and Applications 16(3), 793–810 (1995)
Frandsen, G.S., Sankowski, P.: Dynamic normal forms and dynamic characteristic polynomial. Research Series RS-08-2, BRICS, Department of Computer Science, University of Aarhus (2008), http://www.brics.dk/RS/08/2/index.html
Bürgisser, P., Clausen, M., Shokrollahi, M.: Algebraic complexity theory. Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences], vol. 315. Springer, Berlin (1997)
Bini, D., Pan, V.: Polynomial and Matrix Computations. Birkhäuser (1994)
Eberly, W., Kaltofen, E.: On randomized lanczos algorithms. In: ISSAC 1997: Proceedings of the 1997 international symposium on Symbolic and algebraic com- putation, pp. 176–183. ACM Press, New York (1997)
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Frandsen, G.S., Sankowski, P. (2008). Dynamic Normal Forms and Dynamic Characteristic Polynomial. In: Aceto, L., Damgård, I., Goldberg, L.A., Halldórsson, M.M., Ingólfsdóttir, A., Walukiewicz, I. (eds) Automata, Languages and Programming. ICALP 2008. Lecture Notes in Computer Science, vol 5125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70575-8_36
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DOI: https://doi.org/10.1007/978-3-540-70575-8_36
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