Mark Meckes's papers

Preprints

• The spectra of random abelian G-circulant matrices.
  Submitted.
  arXiv

  Abstract: This paper studies the asymptotic behavior of eigenvalues of random abelian G-circulant matrices, that is, matrices whose structure is related to a finite abelian group G in a way that naturally generalizes the relationship between circulant matrices and cyclic groups. It is shown that, under mild conditions, when the size of the group G goes to infinity, the spectral measures of such random matrices approach a deterministic limit. Depending on some aspects of the structure of the groups, whether the matrices are constrained to be Hermitian, and a few details of the distributions of the matrix entries, the limit measure is either a (complex or real) Gaussian distribution or a mixture of two Gaussian distributions.

• Positive definite metric spaces.
  Submitted.
  arXiv

  Abstract: Magnitude is a numerical invariant of finite metric spaces, recently introduced by T. Leinster, which is analogous in precise senses to the cardinality of finite sets or the Euler characteristic of topological spaces. It has been extended to infinite metric spaces in several a priori distinct ways. This paper develops the theory of a class of metric spaces, positive definite metric spaces, for which magnitude is more tractable than in general. Positive definiteness is a generalization of the classical property of negative type for a metric space, which is known to hold for many interesting classes of spaces. It is proved that all the proposed definitions of magnitude coincide for compact positive definite metric spaces and further results are proved about the behavior of magnitude as a function of such spaces. Finally, some facts about the magnitude of compact subsets of l_pⁿ for p ≤ 2 are proved, generalizing results of Leinster for p=1,2, using properties of these spaces which are somewhat stronger than positive definiteness.

Published and accepted papers

• Concentration and convergence rates for spectral measures of random matrices (with E. Meckes).
  Probab. Theory Related Fields, to appear.
  Published version / arXiv

  Abstract: The topic of this paper is the typical behavior of the spectral measures of large random matrices drawn from several ensembles of interest, including in particular matrices drawn from Haar measure on the classical Lie groups, random compressions of random Hermitian matrices, and the so-called random sum of two independent random matrices. In each case, we estimate the expected Wasserstein distance from the empirical spectral measure to a deterministic reference measure, and prove a concentration result for that distance. As a consequence we obtain almost sure convergence of the empirical spectral measures in all cases.

• Concentration for noncommutative polynomials in random matrices (with S. Szarek).
  Proc. Amer. Math. Soc. 140 (2012), 1803–1813.
  Published version / arXiv

  Abstract: We present a concentration inequality for linear functionals of noncommutative polynomials in random matrices. Our hypotheses cover most standard ensembles, including Gaussian matrices, matrices with independent uniformly bounded entries and unitary or orthogonal matrices.

• Another observation about operator compressions (with E. Meckes).
  Proc. Amer. Math. Soc. 139 (2011), 1433–1439.
  Published version / arXiv

  Abstract: Let T be a self-adjoint operator on a finite dimensional Hilbert space. It is shown that the distribution of the eigenvalues of a compression of T to a subspace of a given dimension is almost the same for almost all subspaces. This is a coordinate-free analogue of a recent result of Chatterjee and Ledoux on principal submatrices. The proof is based on measure concentration and entropy techniques, and the result improves on some aspects of the result of Chatterjee and Ledoux.

• Some results on random circulant matrices.
  High Dimensional Probability V: The Luminy Volume, 213–223, IMS Collections 5, Institute of Mathematical Statistics, Beachwood, OH, 2009.
  Published version / arXiv

  Abstract: This paper considers random (non-Hermitian) circulant matrices, and proves several results analogous to recent theorems on non-Hermitian random matrices with independent entries. In particular, the limiting spectral distribution of a random circulant matrix is shown to be complex normal, and bounds are given for the probability that a circulant sign matrix is singular.

• Gaussian marginals of convex bodies with symmetries.
  Beiträge Algebra Geom. 50 (2009) no. 1, pp. 101–118.
  Published version / arXiv

  Abstract: We prove Gaussian approximation theorems for specific k-dimensional marginals of convex bodies which possess certain symmetries. In particular, we treat bodies which possess a 1-unconditional basis, as well as simplices. Our results extend recent results for 1-dimensional marginals due to E. Meckes and the author.

• On the spectral norm of a random Toeplitz matrix.
  Electron. Commun. Probab. 12 (2007), 315–325.
  Published version / arXiv

  Abstract: Suppose that T_n is a Toeplitz matrix whose entries come from a sequence of independent but not necessarily identically distributed random variables with mean zero. Under some additional tail conditions, we show that the spectral norm of T_n is of the order √(n log n). The same result holds for random Hankel matrices as well as other variants of random Toeplitz matrices which have been studied in the literature.

• The central limit problem for random vectors with symmetries (with E. Meckes).
  J. Theoret. Probab. 20 (2007), 697–720.
  Published version / arXiv
  Note: the preprint contains a section on background on Stein's method which does not appear in the published version. As a result, some theorem numbers are different in the two versions.

  Abstract: Motivated by the central limit problem for convex bodies, we study normal approximation of linear functionals of high-dimensional random vectors with various types of symmetries. In particular, we obtain results for distributions which are coordinatewise symmetric, uniform in a regular simplex, or spherically symmetric. Our proofs are based on Stein's method of exchangeable pairs; as far as we know, this approach has not previously been used in convex geometry and we give a brief introduction to the classical method. The spherically symmetric case is treated by a variation of Stein's method which is adapted for continuous symmetries.

• Some remarks on transportation cost and related inequalities.
  Geometric Aspects of Functional Analysis, 237–244, Lecture Notes in Math. 1910, Springer, Berlin, 2007.
  Published version / arXiv

  Abstract: We discuss transportation cost inequalities for uniform measures on convex bodies, and connections with other geometric and functional inequalities. In particular, we show how transportation inequalities can be applied to the slicing problem, and give a new log-Sobolev-type inequality for bounded domains in Rⁿ.

• Sylvester's problem for symmetric convex bodies and related problems.
  Monatsh. Math. 145 (2005) no. 4, 307–319.
  Published version / arXiv
  Note: The published version contains several references to the literature which are missing in the preprint, and has improved proofs of Propositions 13 and 16.

  Abstract: We consider moments of the normalized volume of a symmetric or nonsymmetric random polytope in a fixed symmetric convex body. We investigate for which bodies these moments are extremized, and calculate exact values in some of the extreme cases. We show that these moments are maximized among planar convex bodies by parallelograms.

• Volumes of symmetric random polytopes.
  Arch. Math. 82 (2004) no. 1, 85–96.
  Published version / arXiv

  Abstract: We consider the moments of the volume of the symmetric convex hull of independent random points in an n-dimensional symmetric convex body. We calculate explicitly the second and fourth moments for n points when the given body is B_qⁿ (and all of the moments for the case q = 2), and derive from these the asymptotic behavior of the expected volume of a random simplex in those bodies.

• Concentration of norms and eigenvalues of random matrices.
  J. Funct. Anal. 211 (2004) no. 2, 508–524.
  Published version / arXiv

  Abstract: We prove concentration results for l_pⁿ operator norms of rectangular random matrices and eigenvalues of self-adjoint random matrices. The random matrices we consider have bounded entries which are independent, up to a possible self-adjointness constraint. Our results are based on an isoperimetric inequality for product spaces due to .