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In 2004, Bowers-Stephenson [2] introduced the inversive distance circle packings as a natural generalization of Thurston's circle packings. They further conjectured the rigidity of infinite inversive distance circle packings in the plane.…

Geometric Topology · Mathematics 2025-07-28 Yanwen Luo , Xu Xu , Siqi Zhang

Riemann normal coordinates (RNC) at a regular event $p_0$ of a spacetime manifold $\mathcal{M}$ are constructed by imposing: (i) $g_{\textsf{ab}}|_{p_0}=\eta_{ab}$, and (ii) $\Gamma^\textsf{a}_{\phantom{\textsf a}\textsf{bc}}|_{p_0}=0$.…

General Relativity and Quantum Cosmology · Physics 2020-06-30 Hari K , Dawood Kothawala

In this paper, we prove generalizations to the L^p setting of the Hardy-Rellich inequalities on domains of R^N with singularity given by the distance function to the boundary. The inequalities we obtain are either sharp in bounded domains,…

Analysis of PDEs · Mathematics 2025-07-04 Cristian Cazacu , Teodor Rugină

Given a bounded convex open set $\Omega\subseteq \mathbb R^N$, we prove that the Poincar\'e-Sobolev constants $\lambda_{p,q}(\Omega)$ can be bounded from below by the $p$-power of the ratio between the perimeter of $\Omega$ and a suitable…

Analysis of PDEs · Mathematics 2026-04-15 Giovanni Pisante , Francesca Prinari

Krivine and Maurey proved in 1981 that every stable Banach space contains almost isometric copies of $\ell_p$, for some $p\in[1,\infty)$. In 1983, Raynaud showed that if a Banach space uniformly embeds into a superstable Banach space, then…

Functional Analysis · Mathematics 2018-03-23 Bruno de Mendonça Braga , Andrew Swift

In the symplectic realm, a distance between open starshaped domains in Liouville manifolds was recently defined. This is the symplectic Banach-Mazur distance. It was proposed by Ostrover and Polterovich and developed by Ostrover,…

Symplectic Geometry · Mathematics 2020-09-17 Thomas Melistas

We introduce a refinement of the persistence diagram, the graded persistence diagram. It is the Mobius inversion of the graded rank function, which is obtained from the rank function using the unary numeral system. Both persistence diagrams…

Algebraic Topology · Mathematics 2022-05-09 Leo Betthauser , Peter Bubenik , Parker B. Edwards

We compute the exact John--Nirenberg constant of ${\rm BMO}^p((0,1))$ for $1\le p\le 2,$ which has been known only for $p=1$ and $p=2.$ We also show that this constant is attained in the weak-type John--Nirenberg inequality and obtain a…

Classical Analysis and ODEs · Mathematics 2015-06-17 Leonid Slavin

We provide, in every infinite-dimensional separable Banach space, an average locally uniformly rotund (and hence rotund) Gateaux smooth renorming which is not locally uniformly rotund. This solves an open problem posed by A.J. Guirao, V.…

Functional Analysis · Mathematics 2024-02-28 Carlo Alberto De Bernardi , Jacopo Somaglia

We introduce a new class of bounded linear operators, called range strongly exposing (RSE) operators, which form a natural intermediate class: weaker than Bourgain's absolutely strongly exposing operators, yet stronger than both uniquely…

Functional Analysis · Mathematics 2025-04-10 Geunsu Choi , Helena del Río , Audrey Fovelle , Mingu Jung , Miguel Martín

For a given Markov chain Monte Carlo (MCMC) algorithm, we define the distance between configurations that quantifies the difficulty of transitions. This distance enables us to investigate MCMC algorithms in a geometrical way, and we…

High Energy Physics - Lattice · Physics 2020-01-08 Masafumi Fukuma , Nobuyuki Matsumoto , Naoya Umeda

A classical result due to Frank and Seiringer asserts that for $1\leq p<\frac Ns$, there exists a sharp constant $\mathcal{C}_{N,s,p}>0$ such that $$…

Analysis of PDEs · Mathematics 2026-05-18 Avas Banerjee , Debdip Ganguly , Vivek Sahu

Let $P=(p_1, p_2, \dots, p_n)$ be a polygonal chain in $\mathbb{R}^d$. The stretch factor of $P$ is the ratio between the total length of $P$ and the distance of its endpoints, $\sum_{i = 1}^{n-1} |p_i p_{i+1}|/|p_1 p_n|$. For a parameter…

Computational Geometry · Computer Science 2023-01-11 Ke Chen , Adrian Dumitrescu , Wolfgang Mulzer , Csaba D. Tóth

Curriculum learning needs example difficulty to proceed from easy to hard. However, the credibility of image difficulty is rarely investigated, which can seriously affect the effectiveness of curricula. In this work, we propose Angular Gap,…

Computer Vision and Pattern Recognition · Computer Science 2022-07-19 Bohua Peng , Mobarakol Islam , Mei Tu

In the past, Takahashi has introduced the James type constants $\mathcal{J}_{\mathcal{X} ,t}(\tau)$. Building upon this foundation, we introduce an innovative skew James type constant, denoted as $\mathcal{J}_t[\tau,\mathcal{X}]$, which is…

Functional Analysis · Mathematics 2025-04-02 Zhiyong Rao , Qi Liu , Qiong Wu , Zhouping Yin , Qichuan Ni

We introduce stronger versions of the usual notions of martingale type p <= 2 and cotype q >= 2 of a Banach space X and show that these concepts are equivalent to uniform p-smoothness and q-convexity, respectively. All these are metric…

Functional Analysis · Mathematics 2007-05-23 Jörg Wenzel

We present an implementation of realistic static friction in molecular dynamics (MD) simulations of granular particles. In our model, to break contacts between two particles, one has to apply a finite amount of force, determined by the…

Condensed Matter · Physics 2009-10-22 Jysoo Lee , Hans J. Herrmann

This paper introduces a new metric and mean on the set of positive semidefinite matrices of fixed-rank. The proposed metric is derived from a well-chosen Riemannian quotient geometry that generalizes the reductive geometry of the positive…

Optimization and Control · Mathematics 2009-10-21 Silvere Bonnabel , Rodolphe Sepulchre

In the present paper we investigate some geometrical properties of the norms in Banach function spaces. Particularly there is shown that if exponent $1/p(\cdot)$ belongs to $BLO^{1/\log}$ then for the norm of corresponding variable exponent…

Functional Analysis · Mathematics 2014-11-14 Tengiz Kopaliani , Nino Samashvili , Shalva Zviadadze

Stochastic gradient descent (SGD) and its variants are widely used and highly effective optimization methods in machine learning, especially for neural network training. By using a single datum or a small subset of the data, selected…

Numerical Analysis · Mathematics 2026-01-21 Bangti Jin , Zeljko Kereta , Yuxin Xia