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We study the landscape complexity of the Hamiltonian $X_N(x) +\frac\mu2 \|x\|^2,$ where $X_{N}$ is a smooth Gaussian process with isotropic increments on $\mathbb R^{N}$. This model describes a single particle on a random potential in…

Probability · Mathematics 2023-07-26 Antonio Auffinger , Qiang Zeng

We analyze the landscape of general smooth Gaussian functions on the sphere in dimension $N$, when $N$ is large. We give an explicit formula for the asymptotic complexity of the mean number of critical points of finite and diverging index…

Probability · Mathematics 2013-12-17 Antonio Auffinger , Gerard Ben Arous

We study the energy landscape near the ground state of a model of a single particle in a random potential with trivial topology. More precisely, we find the large dimensional limit of the Hessian spectrum at the global minimum of the…

Probability · Mathematics 2025-12-16 Hao Xu , Qiang Zeng

In large dimension, we study the asymptotic behavior of the mean number of critical points with index k below a level u for an isotropic centered Gaussian random field defined on a family of subsets of $R^d$ depending on d. We prove the…

Probability · Mathematics 2026-02-10 Jean-Marc Azaïs , Céline Delmas

Let $\mathcal{X}= \{X(t) : t \in \mathbb{R}^N \} $ be an isotropic Gaussian random field with real values.In a first part we study the mean number of critical points of $\mathcal{X}$ with index $k$ using random matrices tools.We obtain an…

Probability · Mathematics 2020-11-30 Jean-Marc Azais , Céline Delmas

We determine the asymptotic law for the fluctuations of the total number of critical points of random Gaussian spherical harmonics in the high degree limit. Our results have implications on the sophistication degree of an appropriate…

Probability · Mathematics 2018-01-09 Valentina Cammarota , Igor Wigman

We calculate the average number of critical points of a Gaussian field on a high-dimensional space as a function of their energy and their index. Our results give a complete picture of the organization of critical points and are of…

Disordered Systems and Neural Networks · Physics 2013-05-29 Alan J. Bray , David S. Dean

In this paper we examine isotropic Gaussian random fields defined on $\mathbb R^N$ satisfying certain conditions. Specifically, we investigate the type of a critical point situated within a small vicinity of another critical point, with…

Probability · Mathematics 2023-10-20 Paul Marriott , Weinan Qi , Yi Shen

We study the free energy of a particle in (arbitrary) high-dimensional Gaussian random potentials with isotropic increments. We prove a computable saddle-point variational representation in terms of a Parisi-type functional for the free…

Probability · Mathematics 2014-02-11 Anton Klimovsky

Gaussian random fields on Euclidean spaces whose variances reach their maximum values at unique points are considered. Exact asymptotic behaviors of probabilities of large absolute maximum of theirs trajectories have been evaluated using…

Probability · Mathematics 2019-04-12 Sergey G. Kobelkov , Vladimir I. Piterbarg

We begin with isotropic Gaussian random fields, and show how the Bochner-Godement theorem gives a natural way to describe their covariance structure. We continue with a study of Mat\'ern processes on Euclidean space, spheres, manifolds and…

Probability · Mathematics 2021-11-24 N. H. Bingham , Tasmin L. Symons

Finding the mean of the total number N_{tot} of critical points for N-dimensional random energy landscapes is reduced to averaging the absolute value of characteristic polynomial of the corresponding Hessian. For any finite N we provide the…

Disordered Systems and Neural Networks · Physics 2009-11-10 Yan V. Fyodorov

We study the distribution of metastable vacua and the likelihood of slow roll inflation in high dimensional random landscapes. We consider two examples of landscapes: a Gaussian random potential and an effective supergravity potential…

High Energy Physics - Theory · Physics 2014-05-02 Thomas C. Bachlechner

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

We study the 3-spin spherical model with mean-field interactions and Gaussian random couplings. For moderate system sizes of up to 20 spins, we obtain all stationary points of the energy landscape by means of the numerical polynomial…

Statistical Mechanics · Physics 2015-03-20 Dhagash Mehta , Daniel A. Stariolo , Michael Kastner

We investigate the complexity of the Hamiltonian in the pure $p$-spin spin glass model accompanied with a polynomial-type potential on $\mathbb{R}^N$. In this Hamiltonian, the Gaussian field is anisotropic, and the potential lacks…

Probability · Mathematics 2026-02-12 Wei-Kuo Chen , Te-Lun Lu , Arnab Sen

Random fields in nature often have, to a good approximation, Gaussian characteristics. We present the mathematical framework for a new and simple method for investigating the non-Gaussian contributions, based on counting the maxima and…

Statistical Mechanics · Physics 2012-10-26 T. H. Beuman , A. M. Turner , V. Vitelli

We compute the expected value of various quantities related to the biparametric singularities of a pair of smooth centered Gaussian random fields on an n-dimensional compact manifold, such as the lengths of the critical curves and contours…

Probability · Mathematics 2022-02-17 Mishal Assif P K

We study a non-relativistic charged particle on the Euclidean plane R^2 subject to a perpendicular constant magnetic field and an R^2-homogeneous random potential in the approximation that the corresponding random Landau Hamiltonian on the…

Mathematical Physics · Physics 2015-06-26 Thomas Hupfer , Hajo Leschke , Simone Warzel

We calculate the density of stationary points and minima of a $N\gg 1$ dimensional Gaussian energy landscape. We use it to show that the point of zero-temperature replica symmetry breaking in the equilibrium statistical mechanics of a…

Disordered Systems and Neural Networks · Physics 2009-11-11 Yan V Fyodorov , H-J Sommers , Ian Williams
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