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Related papers: Non-Euclidean geometry in nature

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A theory of structure is formulated for systems of many structureless classical particles with stable local interactions in Euclidean space. Such systems are shown to have their structure in thermodynamic equilibrium determined exactly by a…

Statistical Mechanics · Physics 2026-02-12 John Çamkıran , Fabian Parsch , Glenn D. Hibbard

We study non-parametric regression estimates for random fields. The data satisfies certain strong mixing conditions and is defined on the regular $N$-dimensional lattice structure. We show consistency and obtain rates of convergence. The…

Statistics Theory · Mathematics 2018-07-06 Johannes T. N. Krebs

We propose a geometric formulation of effective field theories via nonlinear supersymmetry. Non-supersymmetric particles are embedded in constrained superfields governed by a nonlinear sigma model, and operators are collected into…

High Energy Physics - Theory · Physics 2025-05-13 Yu-Tse Lee

We study constraint satisfaction problems on the so-called 'planted' random ensemble. We show that for a certain class of problems, e.g. graph coloring, many of the properties of the usual random ensemble are quantitatively identical in the…

Statistical Mechanics · Physics 2009-06-13 Florent Krzakala , Lenka Zdeborová

In this work, we address some important topological and algebraic aspects of two-qudit states evolving under local unitary operations. The projective invariant subspaces and evolutions are connected with the common elements characterizing…

Quantum Physics · Physics 2015-06-22 L. E. Oxman , A. Z. Khoury

Gaussian graphical models are used throughout the natural sciences, social sciences, and economics to model the statistical relationships between variables of interest in the form of a graph. We here provide a pedagogic introduction to…

Statistics Theory · Mathematics 2017-07-17 Caroline Uhler

Self-organized complex structures in nature, e.g. viral capsids, hierarchical biopolymers, and bacterial flagella, offer efficiency, adaptability, robustness, and multi-functionality. Can we program the self-assembly of three-dimensional…

Soft Condensed Matter · Physics 2022-01-11 Francesco Serafin , Jun Lu , Nicholas Kotov , Kai Sun , Xiaoming Mao

Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical properties of these networks has become increasingly relevant…

Physics and Society · Physics 2015-05-26 Zhihao Wu , Giulia Menichetti , Christoph Rahmede , Ginestra Bianconi

Self-Organizing Maps (SOMs, Kohonen networks) belong to neural network models of the unsupervised class. In this paper, we present the generalized setup for non-Euclidean SOMs. Most data analysts take it for granted to use some subregions…

Machine Learning · Computer Science 2024-08-12 Dorota Celińska-Kopczyńska , Eryk Kopczyński

A 3-dimensional graph-manifold is composed from simple blocks which are products of compact surfaces with boundary by the circle. Its global structure may be as complicated as one likes and is described by a graph which might be an…

Mathematical Physics · Physics 2007-05-23 Sergei Buyalo

We develop a geometric framework to study the structure and function of complex networks. We assume that hyperbolic geometry underlies these networks, and we show that with this assumption, heterogeneous degree distributions and strong…

Statistical Mechanics · Physics 2010-09-14 Dmitri Krioukov , Fragkiskos Papadopoulos , Maksim Kitsak , Amin Vahdat , Marian Boguna

Current practice in parameter space exploration in euclidean space is dominated by randomized sampling or design of experiment methods. The biggest issue with these methods is not keeping track of what part of parameter space has been…

Machine Learning · Computer Science 2023-03-16 Avinash Kumar , Anish Kumar , Sumit Sharma , Surjeet Singh , Kumar Vardhan

Diagrammatic techniques to compute perturbatively the spectral properties of Euclidean Random Matrices in the high-density regime are introduced and discussed in detail. Such techniques are developed in two alternative and very different…

Disordered Systems and Neural Networks · Physics 2011-08-31 T. S. Grigera , V. Martin-Mayor , G. Parisi , P. Urbani , P. Verrocchio

For many materials, a precise knowledge of their dispersion spectra is insufficient to predict their ordered phases and physical responses. Instead, these materials are classified by the geometrical and topological properties of their…

Materials Science · Physics 2021-06-16 Qiong Ma , Adolfo G. Grushin , Kenneth S. Burch

We classify $n$-dimensional geometric graph manifolds with nonnegative scalar curvature, and first show that if $n>3$, the universal cover splits off a codimension 3 Euclidean factor. We then proceed with the classification of the…

Differential Geometry · Mathematics 2021-09-17 Luis Florit , Wolfgang Ziller

We apply methods of nonstandard mathematics in order to regard analytic geometry in a very different way. For example, complex spaces are seen to be the "standard part" of certain algebraic nonstandard schemes. We construct a category of…

Algebraic Geometry · Mathematics 2008-06-27 Adel Khalfallah , Siegmund Kosarew

Theoretical research into many-body quantum systems has mostly focused on regular structures which have a small, simple unit cell and where a vanishingly small number of pairs of the constituents directly interact. Motivated by advances in…

Quantum Physics · Physics 2022-12-06 Joseph Tindall , Amy Searle , Abdulla Alhajri , Dieter Jaksch

These lecture notes present an overview of equilibrium statistical mechanics of classical fluids, with special applications to the structural and thermodynamic properties of systems made of particles interacting via the hard-sphere…

Soft Condensed Matter · Physics 2014-06-24 Andrés Santos

We consider the problem of model selection in Gaussian Markov fields in the sample deficient scenario. In many practically important cases, the underlying networks are embedded into Euclidean spaces. Using the natural geometric structure,…

Machine Learning · Statistics 2018-10-31 Ilya Soloveychik , Vahid Tarokh

Working over imperfect fields, we give a comprehensive classification of genus-one curves that are regular but not geometrically regular, extending the known case of geometrically reduced curves. The description is given intrinsically, in…

Algebraic Geometry · Mathematics 2022-11-09 Stefan Schröer