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We investigate some topological properties of random geometric complexes and random geometric graphs on Riemannian manifolds in the thermodynamic limit. In particular, for random geometric complexes we prove that the normalized counting…

Probability · Mathematics 2020-11-30 Antonio Lerario , Raffaella Mulas

An exact solution to the problem of parametric level statistics in non-Gaussian ensembles of N by N Hermitian random matrices with either soft or strong level confinement is formulated within the framework of the orthogonal polynomial…

Statistical Mechanics · Physics 2009-10-31 E. Kanzieper

We obtain exact analytical expressions for correlations between real zeros of the Kac random polynomial. We show that the zeros in the interval $(-1,1)$ are asymptotically independent of the zeros outside of this interval, and that the…

Mathematical Physics · Physics 2015-06-26 Pavel Bleher , Xiaojun Di

A new technique towards finding asymptotic normalization coefficients in the complex-ranged Gaussian basis is presented. It is shown that a diagonalisation procedure for the total Hamiltonian matrix in the given basis results in…

Nuclear Theory · Physics 2019-10-29 D. A. Sailaubek , O. A. Rubtsova

We show that the zeros of the random power series with i.i.d. real Gaussian coefficients form a Pfaffian point process. We further show that the product moments for absolute values and signatures of the power series can also be expressed by…

Probability · Mathematics 2013-04-17 Sho Matsumoto , Tomoyuki Shirai

The zeros of the random Laurent series $1/\mu - \sum_{j=1}^\infty c_j/z^j$, where each $c_j$ is an independent standard complex Gaussian, is known to correspond to the scaled eigenvalues of a particular additive rank 1 perturbation of a…

Mathematical Physics · Physics 2018-07-19 Peter J. Forrester , Jesper R. Ipsen

Gaussian process (GP) regression is a non-parametric, Bayesian framework to approximate complex models. Standard GP regression can lead to an unbounded model in which some points can take infeasible values. We introduce a new GP method that…

Machine Learning · Statistics 2024-04-04 Didem Kochan , Xiu Yang

We study the two-point correlation $K^m_n(z,w)$ between zeros and critical points of Gaussian random holomorphic sections $s_n$ over K\"ahler manifolds. The critical points are points $\nabla_{h^n} s_n=0$ where $\nabla_{h^n}$ is the smooth…

Probability · Mathematics 2019-08-06 Renjie Feng

Resonances in open quantum systems depending on at least two controllable parameters can show the phenomenon of exceptional points (EPs), where not only the eigenvalues but also the eigenvectors of two or more resonances coalesce. Their…

Quantum Physics · Physics 2024-03-14 Patrick Egenlauf , Patric Rommel , Jörg Main

This paper investigates the approximation of Gaussian random variables in Banach spaces, focusing on the high-probability bounds for the approximation of Gaussian random variables using finitely many observations. We derive non-asymptotic…

Statistics Theory · Mathematics 2025-08-28 Daniel Winkle , Ingo Steinwart , Bernard Haasdonk

We analyze Gaussian analytic functions (GAFs) defined as power series with coefficients modeled by discrete stationary Gaussian processes, utilizing their spectral measures. We revisit some limit theorems for random analytic functions and…

Probability · Mathematics 2025-01-08 Tomoyuki Shirai

Learning in Gaussian Process models occurs through the adaptation of hyperparameters of the mean and the covariance function. The classical approach entails maximizing the marginal likelihood yielding fixed point estimates (an approach…

Machine Learning · Statistics 2020-04-07 Vidhi Lalchand , Carl Edward Rasmussen

Certifying the positivity of trigonometric polynomials is of first importance for design problems in discrete-time signal processing. It is well known from the Riesz-Fej\'ez spectral factorization theorem that any trigonometric univariate…

Symbolic Computation · Computer Science 2023-10-05 Victor Magron , Mohab Safey El Din , Markus Schweighofer , Trung Hieu Vu

We review some recent results on random polynomials and their generalizations in complex and symplectic geometry. The main theme is the universality of statistics of zeros and critical points of (generalized) polynomials of degree $N$ on…

Mathematical Physics · Physics 2007-05-23 Steve Zelditch

We study the annealed complexity of a random Gaussian homogeneous polynomial on the $N$-dimensional unit sphere in the presence of deterministic polynomials that depend on fixed unit vectors and external parameters. In particular, we…

Probability · Mathematics 2023-12-20 Vanessa Piccolo

Random matrices formed from i.i.d. standard real Gaussian entries have the feature that the expected number of real eigenvalues is non-zero. This property persists for products of such matrices, independently chosen, and moreover it is…

Mathematical Physics · Physics 2016-08-16 P. J. Forrester , J. R. Ipsen

Consider a polynomial of large degree n whose coefficients are independent, identically distributed, nondegenerate random variables having zero mean and finite moments of all orders. We show that such a polynomial has exactly k real zeros…

Probability · Mathematics 2017-04-03 Amir Dembo , Bjorn Poonen , Qi-Man Shao , Ofer Zeitouni

Consider a random polynomial $Q_n$ of degree $n+1$ whose zeroes are i.i.d. random variables $\xi_0,\xi_1,\ldots,\xi_n$ in the complex plane. We study the pairing between the zeroes of $Q_n$ and its critical points, i.e. the zeroes of its…

Probability · Mathematics 2018-07-09 Zakhar Kabluchko , Hauke Seidel

We study asymptotic distribution of zeros of random holomorphic sections of high powers of positive line bundles defined over projective homogenous manifolds. We work with a wide class of distributions that includes real and complex…

Complex Variables · Mathematics 2026-05-22 Turgay Bayraktar

Numerical Relativity is a mature field with many applications in Astrophysics, Cosmology and even in Fundamental Physics. As such, we are entering a stage in which new sophisticated methods adapted to open problems are being developed. In…

Computational Physics · Physics 2020-02-27 Daniel Santos-Oliván , Carlos F. Sopuerta