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Even though a lattice and its sublattices have the same group of coincidence isometries, the coincidence index of a coincidence isometry with respect to a lattice $\Lambda_1$ and to a sublattice $\Lambda_2$ may differ. Here, we examine the…

Metric Geometry · Mathematics 2015-12-02 Manuel Joseph C. Loquias , Peter Zeiner

A lattice in Euclidean $d$-space is called well-rounded if it contains $d$ linearly independent vectors of minimal length. This class of lattices is important for various questions, including sphere packing or homology computations. The…

Number Theory · Mathematics 2019-06-25 Michael Baake , Rudolf Scharlau , Peter Zeiner

We present an adaptive algorithm for the computation of quantities of interest involving the solution of a stochastic elliptic PDE where the diffusion coefficient is parametrized by means of a Karhunen-Lo\`eve expansion. The approximation…

Numerical Analysis · Mathematics 2023-07-19 Uta Seidler , Michael Griebel

Many geometric optimization problems can be reduced to finding points in space (centers) minimizing an objective function which continuously depends on the distances from the centers to given input points. Examples are $k$-Means, Geometric…

Computational Geometry · Computer Science 2021-08-26 Vladimir Shenmaier

A new class of self-similar ordered structures with non-crystallographic point symmetries is presented. Each of these structures, named superquasicrystals, is given as a section of a higher-dimensional "crystal" with recursive superlattice…

Materials Science · Physics 2007-05-23 Komajiro Niizeki , Nobuhisa Fujita

In this work we introduce a symmetry classification for electronic density waves which break translational symmetry due to commensurate wave vector modulations. The symmetry classification builds on the concept of extended point groups:…

Strongly Correlated Electrons · Physics 2016-03-08 J. W. F. Venderbos

A wide variety of methods have been used to compute percolation thresholds. In lattice percolation, the most powerful of these methods consists of microcanonical simulations using the union-find algorithm to efficiently determine the…

Statistical Mechanics · Physics 2012-12-11 Stephan Mertens , Cristopher Moore

We describe algorithms which address two classical problems in lattice geometry: the lattice covering and the simultaneous lattice packing-covering problem. Theoretically our algorithms solve the two problems in any fixed dimension d in the…

Metric Geometry · Mathematics 2007-05-23 Achill Schuermann , Frank Vallentin

We study lattices in non-positively curved metric spaces. Borel density is established in that setting as well as a form of Mostow rigidity. A converse to the flat torus theorem is provided. Geometric arithmeticity results are obtained…

Group Theory · Mathematics 2010-01-18 P. -E. Caprace , N. Monod

We show that the symmetry groups of the cut cone Cut(n) and the metric cone Met(n) both consist of the isometries induced by the permutations on {1,...,n}; that is, Is(Cut(n))=Is(Met(n))=Sym(n) for n>4. For n=4 we have…

Metric Geometry · Mathematics 2007-05-23 Antoine Deza , Boris Goldengorin , Dmitrii V. Pasechnik

We provide a non-trivial test of supersymmetry in the random-field Ising model at five spatial dimensions, by means of extensive zero-temperature numerical simulations. Indeed, supersymmetry relates correlation functions in a D-dimensional…

Statistical Mechanics · Physics 2019-06-21 Nikolaos G. Fytas , Victor Martin-Mayor , Giorgio Parisi , Marco Picco , Nicolas Sourlas

For each pair $(Q_i,Q_j)$ of reference points and each real number $r$ there is a unique hyperplane $h \perp Q_iQ_j$ such that $d(P,Q_i)^2 - d(P,Q_j)^2 = r$ for points $P$ in $h$. Take $n$ reference points in $d$-space and for each pair…

Combinatorics · Mathematics 2010-01-26 Thomas Zaslavsky

We study computing geometric problems on uncertain points. An uncertain point is a point that does not have a fixed location, but rather is described by a probability distribution. When these probability distributions are restricted to a…

Computational Geometry · Computer Science 2012-05-03 Allan Jorgensen , Maarten Löffler , Jeff M. Phillips

The statics-dynamics correspondence in spin glasses relate non-equilibrium results on large samples (the experimental realm) with equilibrium quantities computed on small systems (the typical arena for theoretical computations). Here we…

Disordered Systems and Neural Networks · Physics 2015-05-27 Luis Antonio Fernandez , Victor Martin-Mayor

This article presents an automated method to quantify and detect symmetry elements in 2D patterns by means of image processing. Escher's woodcuts, a widely recognized didactic tool for crystallographic education of students, were used to…

Popular Physics · Physics 2019-08-22 Paul Plachinda

We consider the problem of matching a metric space $(X,d_X)$ of size $k$ with a subspace of a metric space $(Y,d_Y)$ of size $n \geq k$, assuming that these two spaces have constant doubling dimension $\delta$. More precisely, given an…

Data Structures and Algorithms · Computer Science 2020-12-22 Corentin Allair , Antoine Vigneron

The correlated Wishart model provides the standard benchmark when analyzing time series of any kind. Unfortunately, the real case, which is the most relevant one in applications, poses serious challenges for analytical calculations. Often…

Mathematical Physics · Physics 2018-08-08 Tim Wirtz , Mario Kieburg , Thomas Guhr

We study the problem of super-resolution of a linear combination of Dirac distributions and their derivatives on a one-dimensional circle from noisy Fourier measurements. Following numerous recent works on the subject, we consider the…

Numerical Analysis · Mathematics 2023-03-21 Dmitry Batenkov , Nuha Diab

We study the critical window of the symmetric binary perceptron, or equivalently, combinatorial discrepancy. Consider the problem of finding a binary vector $\sigma$ satisfying $\|A\sigma\|_\infty \le K$, where $A$ is an $\alpha n \times n$…

Probability · Mathematics 2023-08-10 Dylan J. Altschuler

The Johnson-Lindenstrauss transform is a fundamental method for dimension reduction in Euclidean spaces, that can map any dataset of $n$ points into dimension $O(\log n)$ with low distortion of their distances. This dimension bound is tight…

Data Structures and Algorithms · Computer Science 2026-02-20 Shaofeng H. -C. Jiang , Robert Krauthgamer , Shay Sapir , Sandeep Silwal , Di Yue