Using Elimination Theory to Construct Rigid Matrices

The rigidity of a matrix A for target rank r is the minimum number of entries of A that must be changed to ensure that the rank of the altered matrix is at most r. Since its introduction by Valiant (1977), rigidity and similar rank-robustness functions of matrices have found numerous applications in circuit complexity, communication complexity, and learning complexity. Almost all n × n matrices over an infinite field have a rigidity of (n − r)2. It is a long-standing open question to construct infinite families of explicit matrices even with superlinear rigidity when r = Ω(n).In this paper, we construct an infinite family of complex matrices with the largest possible, i.e., (n − r)2, rigidity. The entries of an n × n matrix in this family are distinct primitive roots of unity of orders roughly exp(n2 log n). To the best of our knowledge, this is the first family of concrete (but not entirely explicit) matrices having maximal rigidity and a succinct algebraic description.Our construction is based on elimination theory of polynomial ideals. In particular, we use results on the existence of polynomials in elimination ideals with effective degree upper bounds (effective Nullstellensatz). Using elementary algebraic geometry, we prove that the dimension of the affine variety of matrices of rigidity at most k is exactly n2 – (n – r)2 + k. Finally, we use elimination theory to examine whether the rigidity function is semicontinuous.

[1]  I. Shafarevich,et al.  Basic algebraic geometry 1 (2nd, revised and expanded ed.) , 1994 .

[2]  Nisheeth K. Vishnoi,et al.  The Geometry of Matrix Rigidity , 2003 .

[3]  W. Brownawell Bounds for the degrees in the Nullstellensatz , 1987 .

[4]  Satyanarayana V. Lokam Quadratic Lower Bounds on Matrix Rigidity , 2006, TAMC.

[5]  Igorʹ Rostislavovich Shafarevich Schemes and complex manifolds , 2013 .

[6]  Alicia Dickenstein,et al.  The membership problem for unmixed polynomial ideals is solvable in single exponential time , 1991, Discret. Appl. Math..

[7]  Satyanarayana V. Lokam Spectral Methods for Matrix Rigidity with Applications to Size-Depth Trade-offs and Communication Complexity , 2001, J. Comput. Syst. Sci..

[8]  Melvin Hochster,et al.  Invariant theory and the generic perfection of determinantal loci , 1971 .

[9]  B. Codenotti Matrix Rigidity , 1999 .

[10]  Giovanni Manzini,et al.  Matrix rank and communication complexity , 2000 .

[11]  Mahdi Cheraghchi On Matrix Rigidity and the Complexity of Linear Forms , 2005, Electron. Colloquium Comput. Complex..

[12]  Joseph H. Silverman,et al.  Diophantine Geometry: An Introduction , 2000 .

[13]  Daniel A. Spielman,et al.  A Remark on Matrix Rigidity , 1997, Inf. Process. Lett..

[14]  Joos Heintz,et al.  Corrigendum: Definability and Fast Quantifier Elimination in Algebraically Closed Fields , 1983, Theor. Comput. Sci..

[15]  Joel Friedman,et al.  A note on matrix rigidity , 1993, Comb..

[16]  Satyanarayana V. Lokam Complexity Lower Bounds using Linear Algebra , 2009, Found. Trends Theor. Comput. Sci..

[17]  Satyanarayana V. Lokam Spectral methods for matrix rigidity with applications to size-depth tradeoffs and communication complexity , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.

[18]  Pavel Pudlák,et al.  Circuit lower bounds and linear codes , 2006, Electron. Colloquium Comput. Complex..

[19]  R. Tennant Algebra , 1941, Nature.

[20]  Abhinav Kumar,et al.  Using Elimination Theory to Construct Rigid Matrices , 2013, computational complexity.

[21]  Martin Raab,et al.  Computing the Dimension of a Polynomial Ideal , 2007 .

[22]  Satyanarayana V. Lokam On the rigidity of Vandermonde matrices , 2000, Theor. Comput. Sci..

[23]  W. Narkiewicz Elementary and Analytic Theory of Algebraic Numbers , 1990 .

[24]  C. Wampler,et al.  Basic Algebraic Geometry , 2005 .

[25]  Satyanarayana V. Lokam,et al.  Relations Between Communication Complexity, Linear Arrangements, and Computational Complexity , 2001, FSTTCS.

[26]  Jürgen Forster,et al.  A linear lower bound on the unbounded error probabilistic communication complexity , 2001, Proceedings 16th Annual IEEE Conference on Computational Complexity.

[27]  T. Willmore Algebraic Geometry , 1973, Nature.

[28]  Joos Heintz,et al.  Testing polynomials which are easy to compute (Extended Abstract) , 1980, STOC '80.

[29]  Leslie G. Valiant,et al.  Graph-Theoretic Arguments in Low-Level Complexity , 1977, MFCS.

[30]  Joe Harris,et al.  The Geometry Of Schemes , 1992 .

[31]  Nathan Linial,et al.  Learning Complexity vs. Communication Complexity , 2008, 2008 23rd Annual IEEE Conference on Computational Complexity.

[32]  David A. Cox,et al.  Ideals, Varieties, and Algorithms: An Introduction to Computational Algebraic Geometry and Commutative Algebra, 3/e (Undergraduate Texts in Mathematics) , 2007 .

[33]  J. Kollár Sharp effective Nullstellensatz , 1988 .

[34]  David A. Cox,et al.  Ideals, Varieties, and Algorithms , 1997 .