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Given a strictly increasing sequence $\Lambda=(\lambda_n)$ of nonegative real numbers, with $\sum_{n=1}^\infty \frac{1}{\lambda_n}<\infty$, the M\"untz spaces $M_\Lambda^p$ are defined as the closure in $L^p([0,1])$ of the monomials…

Functional Analysis · Mathematics 2013-08-19 S. Waleed Noor , Dan Timotin

Given an n-vertex digraph D = (V, A) the Max-k-Ordering problem is to compute a labeling $\ell : V \to [k]$ maximizing the number of forward edges, i.e. edges (u,v) such that $\ell$(u) < $\ell$(v). For different values of k, this reduces to…

Data Structures and Algorithms · Computer Science 2015-07-03 Sreyash Kenkre , Vinayaka Pandit , Manish Purohit , Rishi Saket

We study the non-compact Sobolev embeddings into the optimal scale of Lorentz spaces, $W_0^mL^{p,q}(\Omega) \to L^{\frac{dp}{d - mp},r}(\Omega)$, where $\Omega \subseteq \mathbb{R}^d$, $1 \le m \le d$ and $0<q<r\le\infty$ with $1<p<\frac…

Functional Analysis · Mathematics 2025-02-11 Chian Yeong Chuah , Jan Lang , Liding Yao

Consider a random matrix $H:\mathbb{R}^n\longrightarrow\mathbb{R}^m$. Let $D\geq2$ and let $\{W_l\}_{l=1}^{p}$ be a set of $k$-dimensional affine subspaces of $\mathbb{R}^n$. We ask what is the probability that for all $1\leq l\leq p$ and…

Functional Analysis · Mathematics 2013-08-14 Alon Dmitriyuk , Yehoram Gordon

We establish Dahlberg's perturbation theorem for non-divergence form operators L = A\nabla^2. If L_0 and L_1 are two operators on a Lipschitz domain such that the L^p Dirichlet problem for the operator L_0 is solvable for some p in…

Analysis of PDEs · Mathematics 2011-01-28 Martin Dindos , Treven Wall

We study the extreme and the periodic $L_p$ discrepancy of point sets in the $d$-dimensional unit cube. The extreme discrepancy uses arbitrary sub-intervals of the unit cube as test sets, whereas the periodic discrepancy is based on…

Number Theory · Mathematics 2021-09-14 Ralph Kritzinger , Friedrich Pillichshammer

We establish a geometric framework by transforming a graph $G$ into a $(d-1)$-dimensional CW complex $U^{d-1}(G)$. This construction is achieved by systematically attaching $i$-spheres ($2 \le i \le d-1$) to $G$ according to specific rules,…

Combinatorics · Mathematics 2026-03-13 Qiming Fang , Sihong Shao

We study the asymptotic growth of the diameter of a graph obtained by adding sparse "long" edges to a square box in $\Z^d$. We focus on the cases when an edge between $x$ and $y$ is added with probability decaying with the Euclidean…

Probability · Mathematics 2014-01-31 Marek Biskup

Given a $k$-graph $\Lambda$ and an element $p$ of $\NN^k$, we define the dual $k$-graph, $p\Lambda$. We show that when $\Lambda$ is row-finite and has no sources, the $C^*$-algebras $C^*(\Lambda)$ and $C^*(p\Lambda)$ coincide. We use this…

Operator Algebras · Mathematics 2007-05-23 Stephen Allen , David Pask , Aidan Sims

In this paper, optical and electronic properties of diamond shaped graphene quantum dots (DQDs) have been studied by employing large-scale electron-correlated calculations. The computations have been performed using the \pi-electron…

Mesoscale and Nanoscale Physics · Physics 2015-11-16 Tista Basak , Himanshu Chakraborty , Alok Shukla

The number of embeddings of minimally rigid graphs in $\mathbb{R}^D$ is (by definition) finite, modulo rigid transformations, for every generic choice of edge lengths. Even though various approaches have been proposed to compute it, the gap…

Algebraic Geometry · Mathematics 2020-01-24 Evangelos Bartzos , Ioannis Emiris , Jan Legerský , Elias Tsigaridas

The embedding is an essential step when calculating on the D-Wave machine. In this work we show the hardness of the embedding problem for both types of existing hardware, represented by the Chimera and the Pegasus graphs, containing…

Quantum Physics · Physics 2024-07-24 Elisabeth Lobe , Annette Lutz

To what extent is it possible to visualize high-dimensional data in two- or three-dimensional plots? We reframe this question in terms of embedding $n$-vertex graphs (representing the neighborhood structure of the input points) into metric…

Computational Geometry · Computer Science 2026-01-19 Szymon Snoeck , Noah Bergam , Nakul Verma

We conjecture that all connected graphs of order $n$ have von Neumann entropy at least as great as the star $K_{1,n-1}$ and prove this for almost all graphs of order $n$. We show that connected graphs of order $n$ have R\'enyi 2-entropy at…

Let $G$ be a graph with $p(G)$ pendant vertices and $q(G)$ quasi-pendant vertices. Denote by $m_{L(G)}(\lambda)$ the multiplicity of $\lambda$ as a Laplacian eigenvalue of $G$. Let $\overline{G}$ be the reduced graph of $G$, which can be…

Combinatorics · Mathematics 2025-07-09 Fenglei Tian , Dein Wong

A graph $G$ is embeddable in $\mathbb{R}^d$ if vertices of $G$ can be assigned with points of $\mathbb{R}^d$ in such a way that all pairs of adjacent vertices are at the distance 1. We show that verifying embeddability of a given graph in…

Computational Complexity · Computer Science 2014-10-22 Mikhail Tikhomirov

Let $G = (V,E)$ be an undirected graph with maximum degree $\Delta$ and vertex conductance $\Psi^*(G)$. We show that there exists a symmetric, stochastic matrix $P$, with off-diagonal entries supported on $E$, whose spectral gap…

Probability · Mathematics 2022-03-24 Vishesh Jain , Huy Tuan Pham , Thuy-Duong Vuong

For a family of interpolation norms $\| \cdot \|_{1,2,s}$ on $\mathbb{R}^n$, we provide a distribution over random matrices $\Phi_s \in \mathbb{R}^{m \times n}$ parametrized by sparsity level $s$ such that for a fixed set $X$ of $K$ points…

Data Structures and Algorithms · Computer Science 2015-06-03 Felix Krahmer , Rachel Ward

In this paper we prove that the shape optimization problem $$\min\left\{\lambda_k(\Omega):\ \Omega\subset\R^d,\ \Omega\ \hbox{open},\ P(\Omega)=1,\ |\Omega|<+\infty\right\},$$ has a solution for any $k\in\N$ and dimension $d$. Moreover,…

Analysis of PDEs · Mathematics 2013-10-01 Guido De Philippis , Bozhidar Velichkov

We show an analog to the Fast Johnson-Lindenstrauss Transform for Nearest Neighbor Preserving Embeddings in $\ell_2$. These are sparse, randomized embeddings that preserve the (approximate) nearest neighbors. The dimensionality of the…

Data Structures and Algorithms · Computer Science 2017-07-24 Johan Sivertsen
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