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Finding minima of a real valued non-convex function over a high dimensional space is a major challenge in science. We provide evidence that some such functions that are defined on high dimensional domains have a narrow band of values whose…

Machine Learning · Statistics 2015-04-08 Levent Sagun , V. Ugur Guney , Gerard Ben Arous , Yann LeCun

In this work we introduced a new proposal to study the gravitational lensing theory by spherical lenses, starting from its surface mass density $\Sigma(x)$ written in terms of a decreasing function $f$ of a dimensionless coordinate $x$ on…

Cosmology and Nongalactic Astrophysics · Physics 2014-07-21 Roger Hurtado , Leonardo Castaneda , Juan M. Tejeiro

We use finite size scaling to study Ising spin glasses in two spatial dimensions. The issue of universality is addressed by comparing discrete and continuous probability distributions for the quenched random couplings. The sophisticated…

Disordered Systems and Neural Networks · Physics 2016-07-06 L. A. Fernandez , E. Marinari , V. Martin-Mayor , G. Parisi , J. J. Ruiz-Lorenzo

We describe the interplay of quantum and thermal fluctuations in the infinite-range Heisenberg spin glass. This model is generalized to SU(N) symmetry, and we describe the phase diagram as a function of the spin S and the temperature T. The…

Strongly Correlated Electrons · Physics 2009-10-31 A. Georges , O. Parcollet , S. Sachdev

A collection of algorithms is described for numerically computing with smooth functions defined on the unit sphere. Functions are approximated to essentially machine precision by using a structure-preserving iterative variant of Gaussian…

Numerical Analysis · Mathematics 2016-04-05 Alex Townsend , Heather Wilber , Grady B. Wright

We study the spacial and temporal multiscale properties of complex systems. We present accelerated algorithms for dilute spin glasses and display explicitly their relation to the effective dynamics of specific collective degrees of freedom…

Condensed Matter · Physics 2008-02-03 N. Persky , S. Solomon

Spherical Bessel functions appear commonly in many areas of physics wherein there is both translation and rotation invariance, and often integrals over products of several arise. Thus, analytic evaluation of such integrals with different…

Mathematical Physics · Physics 2023-12-25 Jessica Chellino , Zachary Slepian

The higher characteristics w_m(G) for a finite abstract simplicial complex G are topological invariants that satisfy k-point Green function identities and can be computed in terms of Euler characteristic in the case of closed manifolds,…

Combinatorics · Mathematics 2023-02-07 Oliver Knill

We prove rigidity for hypersurfaces with boundary in the unit $(n+1)$-sphere with scalar curvature bounded below by $n(n-1)$. Under appropriate boundary conditions, the hypersurfaces are shown to be part of the equatorial spheres. The lower…

Differential Geometry · Mathematics 2016-12-28 Lan-Hsuan Huang , Damin Wu

We compute the minimum number of critical points of a small codimension smooth map between two manifolds. We give as well some partial results for the case of higher codimension when the manifolds are spheres.

Geometric Topology · Mathematics 2007-05-23 Dorin Andrica , Louis Funar

This paper develops approximate message passing algorithms to optimize multi-species spherical spin glasses. We first show how to efficiently achieve the algorithmic threshold energy identified in our companion work, thus confirming that…

Probability · Mathematics 2024-01-30 Brice Huang , Mark Sellke

We present a model of spheres moving in a high-dimensional compact space. We relate it to a mixed matrix model with a $O(N)$ invariant model plus a $P(N)$ invariant perturbation. We then study the low pressure regime by performing a…

Condensed Matter · Physics 2009-10-28 Leticia F. Cugliandolo , J. Kurchan , Remi Monasson , Giorgio Parisi

Spin-glass systems are universal models for representing many-body phenomena in statistical physics and computer science. High quality solutions of NP-hard combinatorial optimization problems can be encoded into low energy states of…

Disordered Systems and Neural Networks · Physics 2020-01-14 Gavin S. Hartnett , Masoud Mohseni

We study the landscapes of multi-species spherical spin glasses. Our results determine the phase boundary for annealed trivialization of the number of critical points, and establish its equivalence with a quenched strong topological…

Probability · Mathematics 2025-05-27 Brice Huang , Mark Sellke

In this paper, analytical solutions describing static and spherically symmetric sources in the decoupling limit of massive gravity are derived. We analyze the model parameter range and specify when a Vainshtein mechanism is possible.…

General Relativity and Quantum Cosmology · Physics 2011-11-28 Stefan Sjors , Edvard Mortsell

We analyse the critical region of finite-($d$)-dimensional Ising spin glass, in particular the limit of $d$ closely above the lower critical dimension $d_\ell$. At criticality the thermally active degrees of freedom are surfaces (of width…

Condensed Matter · Physics 2009-10-28 M. J. Thill , H. J. Hilhorst

The scaling of fluctuations in the distribution of ground-state energies or costs with the system size N for Ising spin glasses is considered using an extensive set of simulations with the Extremal Optimization heuristic across a range of…

Disordered Systems and Neural Networks · Physics 2022-05-20 Stefan Boettcher

Spherical symmetry is ubiquitous in nature. It's therefore unfortunate that spherical system simulations are so hard, and require complete spheres with millions of interacting particles. Here we introduce an approach to model spherical…

Materials Science · Physics 2011-10-07 Pekka Koskinen , Oleg O. Kit

Smooth random Gaussian functions play an important role in mathematical physics, a main example being the random plane wave model conjectured by Berry to give a universal description of high-energy eigenfunctions of the Laplacian on generic…

Probability · Mathematics 2018-07-19 Dmitry Beliaev , Stephen Muirhead

The spherical p-spin model is not only a fundamental model in statistical mechanics of disordered system, but has recently gained popularity since many hard problems in machine learning can be mapped on it. Thus the study of the out of…

Disordered Systems and Neural Networks · Physics 2020-09-02 Giampaolo Folena , Silvio Franz , Federico Ricci-Tersenghi