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Covariance operators of random functions are crucial tools to study the way random elements concentrate over their support. The principal component analysis of a random function X is well-known from a theoretical viewpoint and extensively…

Statistics Theory · Mathematics 2016-08-14 André Mas

Covariance estimation for matrix-valued data has received an increasing interest in applications. Unlike previous works that rely heavily on matrix normal distribution assumption and the requirement of fixed matrix size, we propose a class…

Methodology · Statistics 2022-04-20 Yichi Zhang , Weining Shen , Dehan Kong

We establish a direct connection between two fundamental topics: one in probability theory and one in quantum field theory. The first topic is the problem of pointwise multiplication of random Schwartz distributions which has been the…

Probability · Mathematics 2019-11-14 Abdelmalek Abdesselam

Due to recent important work of Zyczkowski and Sommers (quant-ph/0302197 and quant-ph/0304041), exact formulas are available (both in terms of the Hilbert-Schmidt and Bures metrics) for the (n^2-1)-dimensional and (n(n-1)/2-1)-dimensional…

Quantum Physics · Physics 2013-05-29 Paul B. Slater

The variance--covariance matrix plays a central role in the inferential theories of high-dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many…

Methodology · Statistics 2012-03-15 Jianqing Fan , Yuan Liao , Martina Mincheva

The object of this paper is to investigate the certain results involving Bateman's matrix polynomials for integral index. We obtain some properties, integral representation and recurrence relations for hypergeometric matrix function. We…

General Mathematics · Mathematics 2024-07-18 Ghazi S. Khammash , Shimaa I. Moustafa , Shahid Mubeen , Saralees Nadarajah , Ayman Shehata

We introduce a supervised dimensionality reduction methodology for categorical (and discretized mixed-type) data based on a density-matrix construction induced by class-conditional frequencies. Given a labeled dataset encoded in a one-hot…

Machine Learning · Statistics 2026-03-03 Raquel Bosch-Romeu , Antonio Falcó , osé-Antonio Rodríguez-Gallego

A new method to extract the density of partition function zeroes (a continuous function) from their distribution for finite lattices (a discrete data set) is presented. This allows direct determination of the order and strength of phase…

Statistical Mechanics · Physics 2009-11-07 Wolfhard Janke , Ralph Kenna

Statistical depth, a commonly used analytic tool in non-parametric statistics, has been extensively studied for multivariate and functional observations over the past few decades. Although various forms of depth were introduced, they are…

Methodology · Statistics 2019-09-30 Weilong Zhao , Zishen Xu , Yun Yang , Wei Wu

We study the statistics of matrix elements of local operators in the basis of energy eigenstates in a paradigmatic integrable many-particle quantum theory, the Lieb-Liniger model of bosons with repulsive delta-function interaction. Using…

Statistical Mechanics · Physics 2023-07-25 F. H. L. Essler , A. J. J. M. de Klerk

We present a new variational model for computing the electronic first-order density matrix of a crystalline material in presence of a local defect. A natural way to obtain variational discretizations of this model is to expand the…

Other Condensed Matter · Physics 2009-11-13 Eric Cances , Amelie Deleurence , Mathieu Lewin

Linear operators $R$ are introduced on tensor products of evaluation modules of $U'_q\bigl(\widehat{sl}(2)\bigr)$ obtained from the complementary and strange series representations. The operators $R$ satisfy the intertwining condition on…

Exactly Solvable and Integrable Systems · Physics 2015-06-23 R. M. Gade

We denote by $M^n$ the set of $n$ by $n$ complex matrices. Given a fixed density matrix $\beta:\mathbb{C}^n \to \mathbb{C}^n$ and a fixed unitary operator $U : \mathbb{C}^n \otimes \mathbb{C}^n \to \mathbb{C}^n \otimes \mathbb{C}^n$, the…

Mathematical Physics · Physics 2015-05-11 Artur O. Lopes , M. Sebastiani

We aim to give a self-contained and detailed yet simplified account of the foundations of the theory of double operator integrals, in order to provide an accessible entry point to the theory. We make two new contributions to these…

Mathematical Physics · Physics 2025-10-31 Robert Ferydouni , Daniel D. Spiegel

We study statistical properties of a class of band random matrices which naturally appears in systems of interacting particles. The local spectral density is shown to follow the Breit-Wigner distribution in both localized and delocalized…

Condensed Matter · Physics 2009-10-28 Ph. Jacquod , D. L. Shepelyansky

We study partial derivatives on the product of two metric measure structures, in particular in connection with calculus via modules as proposed by the first named author. Our main results are 1) The extension to this non-smooth framework of…

Functional Analysis · Mathematics 2020-12-08 Nicola Gigli , Chiara Rigoni

We connect through the Fourier transform shift-invariant Sobolev type spaces $V_s\subset H^s$, $s\in\mathbb R,$ and the spaces of periodic distributions and analyze the properties of elements in such spaces with respect to the product. If…

Functional Analysis · Mathematics 2024-03-18 Aleksandar Aksentijević , Suzana Aleksić , Stevan Pilipović

In the first part we study critical points of random polynomials. We choose two deterministic sequences of complex numbers,whose empirical measures converge to the same probability measure in complex plane. We make a sequence of polynomials…

Probability · Mathematics 2016-05-05 Tulasi Ram Reddy

Given a pair of distinct non-CM normalized eigenforms having integer Fourier coefficients $a_1 (n)$ and $a_2(n)$, we count positive integers $n$ with $(a_1(n), a_2(n))=1$ and make a conjecture about the density of the set of primes $p$ for…

Number Theory · Mathematics 2022-02-09 Satadal Ganguly , Arvind Kumar , Moni Kumari

Let $X=\{X_n: n\in \mathbb{N}\}$ be a linear process with bounded probability density function $f(x)$. Under certain conditions, we use the kernel estimator \[ \frac{2}{n(n-1)h_n} \sum_{1\le i<j\le n}K\Big(\frac{X_i-X_j}{h_n}\Big) \] to…

Statistics Theory · Mathematics 2024-03-29 Yudan Xiong , Fangjun Xu