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Computer experiments are pivotal for modeling complex real-world systems. Maximizing information extraction and ensuring accurate surrogate modeling necessitates space-filling designs, where design points extensively cover the input domain.…

Methodology · Statistics 2025-08-01 Hui Lan , Xu He

We study the maximum cardinality problem of a set of few distances in the Hamming and Johnson spaces. We formulate semidefinite programs for this problem and extend the 2011 works by Barg-Musin and Musin-Nozaki. As our main result, we find…

Combinatorics · Mathematics 2022-07-08 Alexander Barg , Ching-Yi Lai , Pin-Chieh Tseng , Wei-Hsuan Yu

In previous work the authors defined the k-th order simplicial distance between probability distributions which arises naturally from a measure of dispersion based on the squared volume of random simplices of dimension k. This theory is…

Statistics Theory · Mathematics 2018-09-06 Luc Pronzato , Henry Wynn , Anatoly Zhigljavsky

Subspace codes and particularly constant dimension codes have attracted much attention in recent years due to their applications in random network coding. As a particular subclass of subspace codes, cyclic subspace codes have additional…

Information Theory · Computer Science 2017-07-17 Bocong Chen , Hongwei Liu

Constant dimension codes, with a prescribed minimum distance, have found recently an application in network coding. All the codewords in such a code are subspaces of $\F_q^n$ with a given dimension. A computer search for large constant…

Information Theory · Computer Science 2010-03-26 Natalia Silberstein , Tuvi Etzion

In order to use quantum devices for computations, it is necessary to understand the intricacies of the theoretical description. To this end, we provide several novel constructions useful for the comprehension of quantum mechanics from the…

Quantum Physics · Physics 2022-04-28 Grzegorz Rajchel-Mieldzioć

We study singular 1/2 BPS solutions in M-theory using 11-dimensional superstar solutions. The superstar solutions and their corresponding plane wave limits could give an insight how one may deform the boundary conditions to get singular,…

High Energy Physics - Theory · Physics 2007-05-23 Mohsen Alishahiha , Hossein Yavartanoo

The Wasserstein distance received a lot of attention recently in the community of machine learning, especially for its principled way of comparing distributions. It has found numerous applications in several hard problems, such as domain…

Machine Learning · Statistics 2017-10-23 Nicolas Courty , Rémi Flamary , Mélanie Ducoffe

For each n greater than 7 we explicitly construct a sequence of Stein manifolds diffeomorphic to complex affine space of dimension n so that there is no algorithm to tell us in general whether a given such Stein manifold is symplectomorphic…

Symplectic Geometry · Mathematics 2011-09-22 Mark McLean

The set of all error-correcting codes C over a fixed finite alphabet F of cardinality q determines the set of code points in the unit square with coordinates (R(C), delta (C)):= (relative transmission rate, relative minimal distance). The…

Information Theory · Computer Science 2019-09-04 Yuri I. Manin , Matilde Marcolli

We apply polynomial techniques (linear programming) to obtain lower and upper bounds on the covering radius of spherical designs as function of their dimension, strength, and cardinality. In terms of inner products we improve the lower…

Combinatorics · Mathematics 2020-07-14 Peter Boyvalenkov , Maya Stoyanova

The distribution of visible matter in the universe, such as galaxies and galaxy clusters, has its origin in the week fluctuations of density that existed at the epoch of recombination. The hierarchical distribution of the universe, with its…

Cosmology and Nongalactic Astrophysics · Physics 2015-01-21 Bruce N. Miller , Jean-Louis Rouet , Yui Shiozawa

In this paper, we compare two optimization algorithms using full Hessian and approximation Hessian to obtain numerical spherical designs through their variational characterization. Based on the obtained spherical design point sets, we…

Numerical Analysis · Mathematics 2024-01-03 Yuchen Xiao , Xiaosheng Zhuang

A finite set of unlabelled points in Euclidean space is the simplest representation of many real objects from mineral rocks to sculptures. Since most solid objects are rigid, their natural equivalence is rigid motion or isometry maintaining…

Metric Geometry · Mathematics 2023-03-27 Vitaliy Kurlin

We prove a limit theorem for the the maximal interpoint distance (also called the diameter) for a sample of n i.i.d. points in the unit ball of dimension 2 or more. The exact form of the limit distribution and the required normalisation are…

Probability · Mathematics 2007-05-23 Michael Mayer , Ilya Molchanov

Most of the work on checking spherical symmetry assumptions on the distribution of the $p$-dimensional random vector $Y$ has its focus on statistical tests for the null hypothesis of exact spherical symmetry. In this paper, we take a…

Methodology · Statistics 2026-01-26 Lujia Bai , Holger Dette

For large classes of group testing problems, we derive lower bounds for the probability that all significant items are uniquely identified using specially constructed random designs. These bounds allow us to optimize parameters of the…

Statistics Theory · Mathematics 2022-02-17 Jack Noonan , Anatoly Zhigljavsky

We want to introduce a construction of spherical designs from finite graphs with the theory of crystal lattice. We start from a finite graph, and we consider standard realization of the crystal lattices as the maximal Abelian covering of…

Combinatorics · Mathematics 2008-04-21 Junichi Shigezumi

Near maximum distance separable (NMDS) codes, where both the code and its dual are almost maximum distance separable, play pivotal roles in combinatorial design theory and cryptographic applications. Despite progress in fixed dimensions…

Information Theory · Computer Science 2025-04-10 Yaozong Zhang , Dabin Zheng , Xiaoqiang Wang , Wei Lu

Divergence functions are measures of distance or dissimilarity between probability distributions that serve various purposes in statistics and applications. We propose decompositions of Wasserstein and Cram\'er distances$-$which compare two…

Methodology · Statistics 2025-08-08 Johannes Resin , Daniel Wolffram , Johannes Bracher , Timo Dimitriadis
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