Abstract
We derive a lower bound on the smallest singular value of a random d-regular matrix, that is, the adjacency matrix of a random d-regular directed graph. Specifically, let \(C_1<d< c n/\log ^2 n\) and let \(\mathcal {M}_{n,d}\) be the set of all \(n\times n\) square matrices with 0 / 1 entries, such that each row and each column of every matrix in \(\mathcal {M}_{n,d}\) has exactly d ones. Let M be a random matrix uniformly distributed on \(\mathcal {M}_{n,d}\). Then the smallest singular value \(s_{n} (M)\) of M is greater than \(n^{-6}\) with probability at least \(1-C_2\log ^2 d/\sqrt{d}\), where c, \(C_1\), and \(C_2\) are absolute positive constants independent of any other parameters. Analogous estimates are obtained for matrices of the form \(M-z\,\mathrm{Id}\), where \(\mathrm{Id}\) is the identity matrix and z is a fixed complex number.
Similar content being viewed by others
References
Adamczak, R., Litvak, A.E., Pajor, A., Tomczak-Jaegermann, N.: Quantitative estimates of the convergence of the empirical covariance matrix in log-concave Ensembles. J. Am. Math. Soc. 23, 535–561 (2010)
Adamczak, R., Guedon, O., Litvak, A.E., Pajor, A., Tomczak-Jaegermann, N.: Condition number of a square matrix with i.i.d. columns drawn from a convex body. Proc. Am. Math. Soc. 140, 987–998 (2012)
Bai, Z., Silverstein, J.W.: Spectral Analysis of Large Dimensional Random Matrices, Springer Series in Statistics, 2nd edn. Springer, New York (2010)
Basak, A., Cook, N., Zeitouni, O.: Circular law for the sum of random permutation matrices. Electron. J. Probab. 23(33), 1–51 (2018)
Basak, A., Rudelson, M.: Invertibility of sparse non-hermitian matrices. Adv. Math. 310, 426–483 (2017)
Bau, D., Trefethen, L.: Numerical Linear Algebra. Society for Industrial and Applied Mathematics (SIAM), Philadelphia (1997)
Bordenave, C., Chafaï, D.: Around the circular law. Probab. Surv. 9, 1–89 (2012)
Brazitikos, S., Giannopoulos, A., Valettas, P., Vritsiou, B.: Geometry of Isotropic Convex Bodies. Mathematical Surveys and Monographs, vol. 196. American Mathematical Society, Providence (2014)
Cook, N.A.: Discrepancy properties for random regular digraphs. Random Struct. Algorithms 50(1), 23–58 (2017)
Cook, N.A.: On the singularity of adjacency matrices for random regular digraphs. Probab. Theory Relat. Fields 167(1–2), 143–200 (2017)
Cook, N.: The circular law for random regular digraphs. arXiv:1703.05839
Costello, K.P., Vu, V.: The rank of random graphs. Random Struct. Algorithms 33(3), 269–285 (2008)
Davidson, K.R., Szarek, S.J.: Local Operator Theory, Random Matrices and Banach Spaces. Handbook of the Geometry of Banach Spaces, vol. 1, p. 317366. North-Holland, Amsterdam (2001)
Erdős, P.: On a lemma of Littlewood and Offord. Bull. Am. Math. Soc. 51, 898–902 (1945)
Erdös, L., Yau, H.-T.: A Dynamical Approach to Random Matrix Theory, Courant Lecture Notes in Mathematics, 28. Courant Institute of Mathematical Sciences, New York; American Mathematical Society, Providence, RI (2017)
Frieze, A.: Random structures and algorithms. Proc. ICM 1, 311–340 (2014)
Guedon, O., Litvak, A.E., Pajor, A., Tomczak-Jaegermann, N.: On the interval of fluctuation of the singular values of random matrices. J. Eur. Math. Soc. (JEMS) 19(5), 1469–1505 (2017)
Kashin, B.S.: Diameters of some finite-dimensional sets and classes of smooth functions. Izv. Akad. Nauk SSSR, Ser. Mat. 41, 334–351 (1977)
Kleitman, D.J.: On a Lemma of Littlewood and Offord on the distributions of linear combinations of vectors. Adv. Math. 5, 155–157 (1970)
Koltchinskii, V., Mendelson, S.: Bounding the smallest singular value of a random matrix without concentration. Int. Math. Res. Not. 23, 12991–13008 (2015)
Ledoux, M., Talagrand, M.: Probability in Banach Spaces. Isoperimetry and Processes. Springer, Berlin (1991)
Litvak, A.E., Lytova, A., Tikhomirov, K., Tomczak-Jaegermann, N., Youssef, P.: Adjacency matrices of random digraphs: singularity and anti-concentration. J. Math. Anal. Appl. 445, 1447–1491 (2017)
Litvak, A.E., Lytova, A., Tikhomirov, K., Tomczak-Jaegermann, N., Youssef, P.: Anti-concentration property for random digraphs and invertibility of their adjacency matrices. C.R. Math. Acad. Sci. Paris 354, 121–124 (2016)
Litvak, A.E., Lytova, A., Tikhomirov, K., Tomczak-Jaegermann, N., Youssef, P.: Circular law for sparse random regular digraphs. Submitted
Litvak, A.E., Lytova, A., Tikhomirov, K., Tomczak-Jaegermann, N., Youssef, P.: Structure of eigenvectors of random regular digraphs. Submitted
Litvak, A.E., Lytova, A., Tikhomirov, K., Tomczak-Jaegermann, N., Youssef, P.: The rank of random regular digraphs of constant degree. J. Complex. (2018). https://doi.org/10.1016/j.jco.2018.05.004
Litvak, A.E., Pajor, A., Rudelson, M., Tomczak-Jaegermann, N.: Smallest singular value of random matrices and geometry of random polytopes. Adv. Math. 195, 491–523 (2005)
Litvak, A.E., Pajor, A., Rudelson, M., Tomczak-Jaegermann, N., Vershynin, R.: Random Euclidean embeddings in spaces of bounded volume ratio. C.R. Acad. Sci. Paris, Ser 1, Math. 339, 33–38 (2004)
Mendelson, S., Paouris, G.: On singular values of matrices. J. EMS 16, 823–834 (2014)
Oliveira, R.I.: The lower tail of random quadratic forms, with applications to ordinary least squares and restricted eigenvalue properties. PTRF 166, 1175–1194 (2016)
Rebrova, E., Tikhomirov, K.: Coverings of random ellipsoids, and invertibility of matrices with i.i.d. heavy-tailed entries. Israel J. Math. To appear. arXiv:1508.06690
Rudelson, M., Vershynin, R.: The Littlewood–Offord problem and invertibility of random matrices. Adv. Math. 218, 600–633 (2008)
Rudelson, M., Vershynin, R.: Smallest singular value of a random rectangular matrix. Commun. Pure Appl. Math. 62(12), 1707–1739 (2009)
Rudelson, M., Vershynin, R.: Non-asymptotic theory of random matrices: extreme singular values. In: Proceedings ICM, Vol. III, 1576–1602, Hindustan Book Agency, New Delhi (2010)
Sankar, A., Spielman, D.A., Teng, S.-H.: Smoothed analysis of the condition numbers and growth factors of matrices. SIAM J. Matrix Anal. Appl. 28(2), 446–476 (2006). (electronic)
Schechtman, G.: Special orthogonal splittings of \(L_1^{2k}\). Isr. J. Math. 139, 337–347 (2004)
Smale, S.: On the efficiency of algorithms of analysis. Bull. Am. Math. Soc. (N.S.) 13, 87–121 (1985)
Spielman, D.A., Teng, S.-H.: Smoothed analysis of algorithms. In: Proceedings ICM, vol. I, pp. 597–606. Higher Ed. Press, Beijing (2002)
Srivastava, N., Vershynin, R.: Covariance estimation for distributions with \(2+\varepsilon \) moments. Ann. Probab. 41(5), 3081–3111 (2013)
Tao, T., Vu, V.: The condition number of a randomly perturbed matrix. In: STOC’07—Proceedings of the 39th Annual ACM Symposium on Theory of Computing, pp. 248–255, ACM, New York (2007)
Tao, T., Vu, V.: Inverse Littlewood–Offord theorems and the condition number of random discrete matrices. Ann. Math. 169, 595–632 (2009)
Tao, T., Vu, V.: Smooth analysis of the condition number and the least singular value. Math. Comput. 79(272), 2333–2352 (2010)
Tao, T., Vu, V.: Random matrices: universality of ESDs and the circular law. Ann. Probab. 38(5), 2023–2065 (2010). With an appendix by Manjunath Krishnapur
Tikhomirov, K.: Sample covariance matrices of heavy-tailed distributions. Int. Math. Res. Not. (2017). https://doi.org/10.1093/imrn/rnx067
Tomczak-Jaegermann, N.: Banach–Mazur distances and finite-dimensional operator ideals. Pitman Monographs and Surveys in Pure and Applied Mathematics, 38. Longman Scientific & Technical, Harlow; copublished in the United States with John Wiley & Sons, Inc., New York (1989)
van de Geer, S., Muro, A.: On higher order isotropy conditions and lower bounds for sparse quadratic forms. Electron. J. Stat. 8, 3031–3061 (2014)
von Neumann, J.: Collected works. Vol. V: Design of Computers, Theory of Automata and Numerical Analysis. General editor: A. H. Taub. A Pergamon Press Book The Macmillan Co., New York (1963)
von Neumann, J., Goldstine, H.H.: Numerical inverting of matrices of high order. Bull. Am. Math. Soc. 53, 1021–1099 (1947)
Vu, V.: Random discrete matrices, Horizons of combinatorics, Bolyai Soc. Math. Stud., 17, 257–280, Springer, Berlin (2008)
Vu, V.H.: Combinatorial problems in random matrix theory. In: Proceedings ICM, Vol. IV, pp. 489–508, Kyung Moon Sa, Seoul (2014)
Yaskov, P.: Lower bounds on the smallest eigenvalue of a sample covariance matrix. Electron. Commun. Probab. 19, 1–10 (2014)
Yaskov, P.: Sharp lower bounds on the least singular value of a random matrix without the fourth moment condition. Electron. Commun. Probab. 20(44), 9 (2015)
Acknowledgements
We are grateful to an anonymous referee for careful reading the first draft of the manuscript and many valuable suggestions, which helped us to improve presentation. The second and the third named authors would like to thank University of Alberta for excellent working conditions in January–August 2016, when a significant part of this work was done.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Litvak, A.E., Lytova, A., Tikhomirov, K. et al. The smallest singular value of a shifted d-regular random square matrix. Probab. Theory Relat. Fields 173, 1301–1347 (2019). https://doi.org/10.1007/s00440-018-0852-y
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00440-018-0852-y
Keywords
- Adjacency matrices
- Anti-concentration
- Condition number
- Invertibility
- Littlewood–Offord theory
- Random graphs
- Random matrices
- Regular graphs
- Singular probability
- Singularity
- Sparse matrices
- Smallest singular value