The least singular value of a random symmetric matrix
Forum of Mathematics, Pi, Tome 12 (2024)

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Let A be an $n \times n$ symmetric matrix with $(A_{i,j})_{i\leqslant j}$ independent and identically distributed according to a subgaussian distribution. We show that

$ \begin{align*}\mathbb{P}(\sigma_{\min}(A) \leqslant \varepsilon n^{-1/2} ) \leqslant C \varepsilon + e^{-cn},\end{align*} $

where $\sigma _{\min }(A)$ denotes the least singular value of A and the constants $C,c>0 $ depend only on the distribution of the entries of A. This result confirms the folklore conjecture on the lower tail of the least singular value of such matrices and is best possible up to the dependence of the constants on the distribution of $A_{i,j}$. Along the way, we prove that the probability that A has a repeated eigenvalue is $e^{-\Omega (n)}$, thus confirming a conjecture of Nguyen, Tao and Vu [Probab. Theory Relat. Fields 167 (2017), 777–816].
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Marcelo Campos; Matthew Jenssen; Marcus Michelen; Julian Sahasrabudhe. The least singular value of a random symmetric matrix. Forum of Mathematics, Pi, Tome 12 (2024). doi: 10.1017/fmp.2023.29

[1] Berkowitz, R., ‘A local limit theorem for cliques in G(n,p)’, Preprint, 2018, .Google Scholar | arXiv

[2] Bourgade, P., Erdős, L., Yau, H.-T. and Yin, J., ‘Fixed energy universality for generalized Wigner matrices’, Comm. Pure Appl. Math. 69(10) (2016), 1815–1881.Google Scholar

[3] Campos, M., Jenssen, M., Michelen, M. and Sahasrabudhe, J., ‘Singularity of random symmetric matrices revisited’, Proc. of Amer. Math. Soc. 150(757) (2021), 3147–3159.Google Scholar

[4] Campos, M., Jenssen, M., Michelen, M. and Sahasrabudhe, J., ‘The singularity probability of a random symmetric matrix is exponentially small’, Preprint, 2021, .Google Scholar | arXiv

[5] Campos, M., Mattos, L., Morris, R. and Morrison, N., ‘On the singularity of random symmetric matrices’, Duke Math. J. 170(5) (2021), 881–907.Google Scholar

[6] Costello, K. P., ‘Bilinear and quadratic variants on the Littlewood-Offord problem’, Isr. J. Math. 194(1) (2013), 359–394.Google Scholar

[7] Costello, K. P., Tao, T. and Vu, V., ‘Random symmetric matrices are almost surely nonsingular’, Duke Math. J. 135(2) (2006), 395–413.Google Scholar

[8] Edelman, A., ‘Eigenvalues and condition numbers of random matrices’, SIAM J. Matrix Anal. Appl. 9(4) (1988), 543–560.Google Scholar

[9] Erdős, L., Ramírez, J., Schlein, B., Tao, T., Vu, V. and Yau, H.-T., ‘Bulk universality for Wigner Hermitian matrices with subexponential decay’, Math. Res. Lett. 17(4) (2010), 667–674.Google Scholar

[10] Erdős, L., Schlein, B. and Yau, H.-T., ‘Local semicircle law and complete delocalization for Wigner random matrices’, Comm. Math. Phys. 287(2) (2009), 641–655.Google Scholar

[11] Erdős, L., Schlein, B. and Yau, H.-T., ‘Semicircle law on short scales and delocalization of eigenvectors for Wigner random matrices’, Ann. Probab. 37(3) (2009), 815–852.Google Scholar | DOI

[12] Erdős, L., ‘Universality of Wigner random matrices: A survey of recent results’, Russ. Math. Surv. 66(3) (2011), 507.Google Scholar | DOI

[13] Erdős, L., Schlein, B. and Yau, H.-T., ‘Wegner estimate and level repulsion for Wigner random matrices’, Int. Math. Res. Not. 2010(3) (2010), 436–479.Google Scholar | DOI

[14] Esseen, C., ‘On the Kolmogorov-Rogozin inequality for the concentration function’, Z. Wahrscheinlichkeitstheor. Verw. Geb. 5(3) (1966), 210–216.Google Scholar

[15] Feldheim, O. N. and Sodin, S., ‘A universality result for the smallest eigenvalues of certain sample covariance matrices’, Geom. Funct. Anal. 20(1) (2010), 88–123.Google Scholar

[16] Ferber, A. and Jain, V., ‘Singularity of random symmetric matrices—A combinatorial approach to improved bounds’, Forum Math. Sigma 7 (2019), Paper No. e22, 29.Google Scholar

[17] Ferber, A., Jain, V., Luh, K. and Samotij, W., ‘On the counting problem in inverse Littlewood–Offord theory’, J. London Math. Soc. 103(4) (2021), 1333–1362.Google Scholar

[18] Hanson, D. L. and Wright, F. T., ‘A bound on tail probabilities for quadratic forms in independent random variables’, Ann. Math. Stat. 42(3) (1971), 1079–1083.Google Scholar | DOI

[19] Jain, V., Sah, A. and Sawhney, M., ‘On the smallest singular value of symmetric random matrices’, Comb. Probab. Comput. 31(4) (2022), 662–683.Google Scholar | DOI

[20] Kwan, M. and Sauermann, L., ‘An algebraic inverse theorem for the quadratic Littlewood-Offord problem, and an application to Ramsey graphs’, Discret. Anal. (2020), Paper No. 12, 34, .Google Scholar | arXiv

[21] Livshyts, G. V., ‘The smallest singular value of heavy-tailed not necessarily i.i.d. random matrices via random rounding’, J. Anal. Math. 145 (2021), 257–306.Google Scholar | DOI

[22] Livshyts, G. V., Tikhomirov, K. and Vershynin, R., ‘The smallest singular value of inhomogeneous square random matrices’, Ann. Probab. 49(3) (2021), 1286–1309.Google Scholar

[23] Meka, R., Nguyen, O. and Vu, V., ‘Anti-concentration for polynomials of independent random variables’, Theory Comput. 12(11) (2016), 1–17.Google Scholar

[24] Nguyen, H., Tao, T. and Vu, V., ‘Random matrices: Tail bounds for gaps between eigenvalues’, Probab. Theory Relat. Fields 167(3) (2017), 777–816.Google Scholar

[25] Nguyen, H. H., ‘Inverse Littlewood-Offord problems and the singularity of random symmetric matrices’, Duke Math. J. 161(4) (2012), 545–586.Google Scholar | DOI

[26] Nguyen, H. H., ‘On the least singular value of random symmetric matrices’, Electron. J. Probab. 17(53) (2012), 19.Google Scholar

[27] Nguyen, H. H., ‘Random matrices: Overcrowding estimates for the spectrum’, J. Funct. Anal. 275(8) (2018), 2197–2224.Google Scholar

[28] Nguyen, H. H. and Vu, V. H., ‘Small probability, inverse theorems, and applications’, in Erdös centennial, Bolyai Society Mathematical Studies, vol. 25 (János Bolyai Mathematical Society, Budapest, 2013), 409–463.Google Scholar

[29] Rebrova, E. and Tikhomirov, K., ‘Coverings of random ellipsoids, and invertibility of matrices with i.i.d. heavy-tailed entries’, Isr. J. Math. 227(2) (2018), 507–544.Google Scholar

[30] Rudelson, M., ‘Invertibility of random matrices: Norm of the inverse’, Ann. of Math. (2) 168(2) (2008), 575–600.Google Scholar

[31] Rudelson, M. and Vershynin, R., ‘The Littlewood-Offord problem and invertibility of random matrices’, Adv. Math. 218(2) (2008), 600–633.Google Scholar | DOI

[32] Rudelson, M. and Vershynin, R., ‘Smallest singular value of a random rectangular matrix’, Comm. Pure Appl. Math. 62(12) (2009), 1707–1739.Google Scholar

[33] Rudelson, M. and Vershynin, R., ‘Hanson-Wright inequality and sub-Gaussian concentration’, Preprint, 2013, .Google Scholar | arXiv

[34] Rudelson, M. and Vershynin, R., ‘Small ball probabilities for linear images of high-dimensional distributions’, Int. Math. Res. Not. 2015(19) (2015), 9594–9617.Google Scholar

[35] Rudelson, M. and Vershynin, R., ‘No-gaps delocalization for general random matrices’, Geom. Funct. Anal. 26(6) (2016), 1716–1776.Google Scholar

[36] Smale, S., ‘On the efficiency of algorithms of analysis’, Bull. Am. Math. Soc. 13(2) (1985), 87–121.Google Scholar

[37] Spielman, D. and Teng, S.-H., ‘Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time’, in Proceedings of the Annual ACM Symposium on Theory of Computing (ACM, New York, 2001), 296–305.Google Scholar

[38] Spielman, D. A. and Teng, S.-H., ‘Smoothed analysis of algorithms’, in Proceedings of the International Congress of Mathematicians, Vol. I (Beijing, 2002) (Higher Education Press, Beijing, 2002), 597–606.Google Scholar

[39] Szarek, S. J., ‘Spaces with large distance to and random matrices’, Amer. J. Math. 112(6) (1990), 899–942.Google Scholar | DOI

[40] Tao, T. and Vu, V., ‘Random matrices: A general approach for the least singular value problem’, Preprint, 2008, .Google Scholar | arXiv

[41] Tao, T. and Vu, V., ‘Random matrices: The distribution of the smallest singular values’, Geom. Funct. Anal. 20(1) (2010), 260–297.Google Scholar

[42] Tao, T. and Vu, V., ‘Random matrices: Universality of local eigenvalue statistics’, Acta Math. 206(1), (2011), 127–204.Google Scholar | DOI

[43] Tao, T. and Vu, V., ‘Random matrices have simple spectrum’, Combinatorica 37(3) (2017) 539–553.Google Scholar

[44] Tao, T. and Vu, V. H., ‘Inverse Littlewood-Offord theorems and the condition number of random discrete matrices’, Ann. of Math. (2) 169(2) (2009), 595–632.Google Scholar

[45] Tikhomirov, K., ‘Singularity of random Bernoulli matrices’, Ann. of Math. 191(2) (2020), 593–634.Google Scholar

[46] Vershynin, R., ‘Invertibility of symmetric random matrices’, Rand. Struct. Algorithms 44(2) (2014), 135–182.Google Scholar

[47] Vershynin, R., High-Dimensional Probability: An Introduction With Applications in Data Science, vol. 47 (Cambridge University Press, Cambridge, 2018).Google Scholar

[48] Von Neumann, J., Design of Computers, Theory of Automata and Numerical Analysis, vol. 5 (Pergamon Press, London, 1963).Google Scholar

[49] Vu, V. H. and Tao, T., ‘The condition number of a randomly perturbed matrix’, in Proceedings of the Annual ACM Symposium on Theory of Computing, STOC ’07 (Association for Computing Machinery, New York, NY, USA, 2007), 248–255.Google Scholar

[50] Wigner, E. P., ‘On the distribution of the roots of certain symmetric matrices’, Ann. of Math. (2) 67(2) (1958), 325–327.Google Scholar

[51] Wright, F. T., ‘A bound on tail probabilities for quadratic forms in independent random variables whose distributions are not necessarily symmetric’, Ann. Probab. 1(6) (1973), 1068–1070.Google Scholar | DOI

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