SearcharxivSearch

arXiv subjects

Vladislav Kargin

Publications and source records attributed to Vladislav Kargin.

At least 19 recordsLinked to original sources

Singularities of matrix semicircles

Let $S=\sum_{i=1}^r A_i\otimes s_i$ be a matrix semicircular element, with Hermitian coefficients $A_i\in M_n(\mathbb{C})$ and free standard semicircular generators $s_i$. Its scalar spectral density $f$ is governed, through Speicher's equation (a matrix Dyson equation), by the completely positive covariance map $\eta_S(X)=\sum_i A_iXA_i$. We treat the singular regime, where the pencil $\sum_i A_i x_i$ is full but not semisimple and $f$ is unbounded at the origin, in contrast to the bounded real-analytic density of the regular case. We prove three results. (i) The leading singularity exponent at $0$ is invariant under congruence $A_i\mapsto bA_ib^{*}$ of the pencil ($b$ invertible), and more generally under symmetric scaling of the covariance map. (ii) For binary elements ($r=2$) we obtain a complete classification: in Lancaster-Rodman canonical form every indecomposable cell is of one of three types, and $f(x)\sim c|x|^{-(n^*-1)/(n^*+1)}$ as $x\to0$ with an explicit constant $c$, where the exponent depends only on the size of the largest Jordan block (the effective chain length $n^*$) and not on the coupling. With (i) and the direct-sum behaviour, this classifies all full binary Hermitian pencils. (iii) The spectral classification is strictly coarser than the algebraic one: a Type III cell of size $2m$ with non-real $\beta$ and the direct sum of two Type II cells of size $m$ with parameter $|\beta|$ have identical scalar densities, yet their covariance maps are not symmetrically scalable; the scalar spectrum cannot detect the phase of $\beta$. Each type calls for a different method: a reduction of Speicher's equation to an autonomous discrete Painlev\'e I (McMillan) map (Type I), a Lyapunov-Schmidt reduction at the branch point (Type II), and a gauge reduction by a diagonal unitary (Type III).

math.OA

An algebraic characterization of non-singular matrix semicircles

Let $A_1, \ldots, A_r$ be Hermitian $n \times n$ matrices and $S = \sum A_i \otimes s_i$ the associated matrix semicircle, where $s_1, \ldots, s_r$ are free semicircular variables. We prove that the following are equivalent: (i) the matrix pencil $A = \sum A_i x_i$ is LR-semisimple (decomposes, up to left--right equivalence, as a direct sum of unsplittable pencils); (ii) $S$ is non-singular at $t = 0$ (the matrix-valued Cauchy transform has a continuous boundary limit near the origin); (iii) the covariance map $η\colon X \mapsto \sum A_i X A_i$ is symmetrically DS-scalable (there exists $C \succ 0$ with $η(C) = C^{-1}$). When these hold, the spectral density satisfies $f(0) = \frac{1}π\,\mathrm{tr}(C)$, where $C$ is the unique trace minimizer of the solution set $\{W \succ 0 : η(W)\,W = I\}$. The proof combines algebraic and analytic ingredients. On the algebraic side, we establish the equivalence (i) $\Leftrightarrow$ (iii) using Gurvits' capacity theory for indecomposable maps and a geodesic reflection theorem in the Riemannian manifold of positive definite matrices, which upgrades DS-scalability to symmetric DS-scalability for self-adjoint completely positive maps. On the analytic side, we prove (iii) $\Rightarrow$ (ii) via a Lyapunov--Schmidt reduction of Speicher's equation at a trace-minimizing solution, showing that the Jacobian of the bifurcation equations is positive definite. This removes a stability hypothesis that was required in earlier approaches.

math.OA

Free compressions of R-diagonal random variables and the semigroup of Brown measures

We investigate the Brown measures of compressions of $R$-diagonal random variables, extending previous results to include unbounded cases. For random variables with finite variance, we demonstrate that the Brown measures of their compressions converge to the uniform distribution on the unit disc. In the case of infinite variance, we characterize the Brown measures that remain stable under the compression operation and explore their properties in detail.

math.PR

Lecture Notes on Free Probability

These lecture notes provide an introduction to free probability theory, with a focus on tools and techniques useful in the study of large random matrices. Topics include freeness, free cumulants, additive and multiplicative free convolution, the R- and S-transforms, subordination theory, and operator-valued extensions. Applications to asymptotic freeness and linearization methods are discussed in detail. The notes aim to be accessible to graduate students with a background in functional analysis and probability. The lecture notes were originally written for a graduate course. They are updated to include recent results on subordination and linearization methods in free probability.

math.PR

The smallest singular value of large random rectangular Toeplitz and circulant matrices

Let $x_i$, $i\in\mathbb{Z}$ be a sequence of i.i.d. standard normal random variables. Consider rectangular Toeplitz $\mathbf{X}=\left(x_{j-i}\right)_{1\leq i\leq p,1\leq j\leq n}$ and circulant $\mathbf{X}=\left(x_{(j-i)\mod n}\right)_{1\leq i\leq p,1\leq j\leq n}$ matrices. Let $p,n\rightarrow\infty$ so that $p/n\rightarrow c\in(0,1]$. We prove that the smallest eigenvalue of $\frac{1}{n}\mathbf{X}\mathbf{X}^\top$ converges to zero in probability and in expectation. We establish a lower bound on the rate of this convergence. The lower bound is faster than any poly-log but slower than any polynomial rate. For the ``rectangular circulant'' matrices, we also establish a polynomial upper bound on the convergence rate, which is a simple explicit function of $c$.

math.PR

An upper bound on the per-tile entropy of ribbon tilings

This paper considers $n$-ribbon tilings of general regions and their per-tile entropy (the binary logarithm of the number of tilings divided by the number of tiles). We show that the per-tile entropy is bounded above by $\log_2 n$. This bound improves the best previously known bounds of $n-1$ for general regions, and the asymptotic upper bound of $\log_2 (en)$ for growing rectangles, due to Chen and Kargin.

math.CO

Scaling limits of slim and fat trees

We consider Galton--Watson trees conditioned on both the total number of vertices $n$ and the number of leaves $k$. The focus is on the case in which both $k$ and $n$ grow to infinity and $k = αn + O(1)$, with $α\in (0, 1)$. Assuming the exponential decay of the offspring distribution, we show that the rescaled random tree converges in distribution to Aldous' Continuum Random Tree with respect to the Gromov--Hausdorff topology. The scaling depends on a parameter $σ^\ast$ which we calculate explicitly. Additionally, we compute the limit for the degree sequences of these random trees.

math.PR

The Number of Ribbon Tilings for Strips

First, we consider order-$n$ ribbon tilings of an $M$-by-$N$ rectangle $R_{M,N}$ where $M$ and $N$ are much larger than $n$. We prove the existence of the growth rate $γ_n$ of the number of tilings and show that $γ_n \leq (n-1) \ln 2$. Then, we study a rectangle $R_{M,N}$ with fixed width $M=n$, called a strip. We derive lower and upper bounds on the growth rate $μ_n$ for strips as $ \ln n - 1 + o(1) \leq μ_n \leq \ln n $. Besides, we construct a recursive system which enables us to enumerate the order-$n$ ribbon tilings of a strip for all $n \leq 8$ and calculate the corresponding generating functions.

math.CO

On enumeration and entropy of ribbon tilings

The paper considers ribbon tilings of large regions and their per-tile entropy (the logarithm of the number of tilings divided by the number of tiles). For tilings of general regions by ribbon tiles of length $n$, we give an upper bound on the per-tile entropy as $n - 1$. For growing rectangular regions, we prove the existence of the asymptotic per-tile entropy and show that it is bounded from below by $\log_2 (n/e)$ and from above by $\log_2(en)$. For growing generalized "Aztec Diamond'' regions and for growing "stair'' regions, the asymptotic per-tile entropy is calculated exactly as $1/2$ and $\log_2(n + 1) - 1$, respectively.

math.PR

Cycles in random meander systems

A meander system is a union of two arc systems that represent non-crossing pairings of the set $[2n] = \{1, \ldots, 2n\}$ in the upper and lower half-plane. In this paper, we consider random meander systems. We show that for a class of random meander systems, -- for simply-generated meander systems, -- the number of cycles in a system of size $n$ grows linearly with $n$ and that the length of the largest cycle in a uniformly random meander system grows at least as $c \log n$ with $c > 0$. We also present numerical evidence suggesting that in a simply-generated meander system of size $n$, (i) the number of cycles of length $k \ll n$ is $\sim n k^{-β}$, where $β\approx 2$, and (ii) the length of the largest cycle is $\sim n^α$, where $α$ is close to $4/5$. We compare these results with the growth rates in other families of meander systems, which we call rainbow meanders and comb-like meanders, and which show significantly different behavior.

math.PR

Limit theorems for statistics of non-crossing partitions

We study the distribution of several statistics of large non-crossing partitions. First, we prove the Gaussian limit theorem for the number of blocks of a given fixed size. In contrast to the properties of usual set partitions, we show that the number of blocks of different sizes are negatively correlated, even for large partitions. In addition, we show that the sizes of blocks in a given large non-crossing partition are distributed according to a geometric distribution and not Poisson, as in the case of usual set partitions. Next, we show that the size of the largest block concentrates at $\log_2 n$, and that after an appropriate rescaling, it can be described by the double exponential distribution. Finally, we show that the width of a large non-crossing partition converges to the Theta-distribution which arises in the theory of Brownian excursions.

math.PR

A 3D Ginibre point field

We introduce a three-dimensional random point field using the concept of the quaternion determinant. Orthogonal polynomials on the space of pure quaternions are defined, and used to construct a kernel function similar to the Ginibre kernel. We find explicit formulas for the polynomials and the kernel, and calculate their asymptotics in the bulk and at the center of coordinates.

math.PR

Limit theorems for linear eigenvalue statistics of overlapping matrices

The paper proves several limit theorems for linear eigenvalue statistics of overlapping Wigner and sample covariance matrices. It is shown that the covariance of the limiting multivariate Gaussian distribution is diagonalized by choosing the Chebyshev polynomials of the first kind as the basis for the test function space. The covariance of linear statistics for the Chebyshev polynomials of sufficiently high degree depends only on the first two moments of the matrix entries. Proofs are based on a graph-theoretic interpretation of the Chebyshev linear statistics as sums over non-backtracking cyclic paths

math.PR

On estimation in the reduced-rank regression with a large number of responses and predictors

We consider a multivariate linear response regression in which the number of responses and predictors is large and comparable with the number of observations, and the rank of the matrix of regression coefficients is assumed to be small. We study the distribution of singular values for the matrix of regression coefficients and for the matrix of predicted responses. For both matrices, it is found that the limit distribution of the largest singular value is a rescaling of the Tracy-Widom distribution. Based on this result, we suggest algorithms for the model rank selection and compare them with the algorithm suggested by Bunea, She and Wegkamp. Next, we design two consistent estimators for the singular values of the coefficient matrix, compare them, and derive the asymptotic distribution for one of these estimators..

math.ST

Variation of word frequencies in Russian literary texts

We study the variation of word frequencies in Russian literary texts. Our findings indicate that the standard deviation of a word's frequency across texts depends on its average frequency according to a power law with exponent $0.62,$ showing that the rarer words have a relatively larger degree of frequency volatility (i.e., "burstiness"). Several latent factors models have been estimated to investigate the structure of the word frequency distribution. The dependence of a word's frequency volatility on its average frequency can be explained by the asymmetry in the distribution of latent factors.

cs.CL

On Fluctuations of Riemann's Zeta Zeros

It is shown that the normalized fluctuations of Riemann's zeta zeros around their predicted locations follow the Gaussian law. It is also shown that fluctuations of two zeros, $γ_{k}$ and $γ_{k+x},$ with $x\sim(\log k)^β$, $β>0$, for large $k$ follow the two-variate Gaussian distribution with correlation $(1-β)_{+}$.

math.PR