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This paper continues the study of a class of compact convex hypersurfaces in Euclidean space $R^{n+1}, ~n \geq 1$, which are boundaries of compact convex bodies obtained by taking the intersection of (solid) confocal paraboloids of…

Differential Geometry · Mathematics 2007-05-23 Vladimir Oliker

Efficient representations of convex sets are of crucial importance for many algorithms that work with them. It is well-known that sometimes, a complicated convex set can be expressed as the projection of a much simpler set in higher…

Optimization and Control · Mathematics 2018-03-23 Rekha R. Thomas

There are three types of results in this paper. The first, extending a representation theorem on a conformal mapping that omits two values of equal modulus. This was due to Brickman and Wilken. They constructed a representation as a convex…

Complex Variables · Mathematics 2019-01-30 Ronen Peretz

Let $\beta_1,...,\beta_n$ be distinct points in the open unit disc in the complex plane, none of which is the origin, and let $H^1$ be the Hardy space. Define a closed convex set in $\mathbb{C}^{n}$ by $\Lambda = \{…

Complex Variables · Mathematics 2020-02-06 Stephen D. Fisher

We shall prove a convergence result relative to sequences of Minkowski symmetrals of general compact sets. In particular, we investigate the case when this process is induced by sequences of subspaces whose elements belong to a finite…

Metric Geometry · Mathematics 2021-12-07 Jacopo Ulivelli

It is well known from the Perron-Frobenius theory that the spectral gap of a positive square matrix is positive. In this paper, we give a more quantitative characterization of the spectral gap. More specifically, using a complex extension…

Spectral Theory · Mathematics 2019-07-17 Wendi Han , Guangyue Han

Minkowski tensors are comprehensive shape descriptors that robustly capture n-point information in complex random geometries and that have already been extensively applied in the Euclidean plane. Here, we devise a novel framework for…

Instrumentation and Methods for Astrophysics · Physics 2024-07-30 Caroline Collischon , Michael Klatt , Anthony Banday , Manami Sasaki , Christoph Räth

We generalize some aspects of the theory of compact projections relative to a C*-algebra, to the setting of more general algebras. Our main result is that compact projections are the decreasing limits of `peak projections', and in the…

Operator Algebras · Mathematics 2012-03-19 David P. Blecher , Matthew Neal

Steiner and Schwarz symmetrizations, and their most important relatives, the Minkowski, Minkowski-Blaschke, fiber, inner rotational, and outer rotational symmetrizations, are investigated. The focus is on the convergence of successive…

Metric Geometry · Mathematics 2022-05-06 Gabriele Bianchi , Richard J. Gardner , Paolo Gronchi

In this paper, we establish a min-max theory for constructing minimal disks with free boundary in any closed Riemannian manifold. The main result is an effective version of the partial Morse theory for minimal disks with free boundary…

Analysis of PDEs · Mathematics 2020-04-01 Longzhi Lin , Ao Sun , Xin Zhou

We prove, under a certain representation theoretic assumption, that the set of real symmetric matrices, whose eigenvalues satisfy a linear matrix inequality, is itself a spectrahedron. The main application is that derivative relaxations of…

Algebraic Geometry · Mathematics 2022-10-04 Mario Kummer

This paper describes the expected characteristic polynomial of the commutator of randomly rotated matrices, in the context of the finite free probability theory initiated by Marcus, Spielman, and Srivastava. The key technical features are…

Combinatorics · Mathematics 2022-09-02 Jacob Campbell

This paper extends the Kadison duality between compact convex sets and function systems to the setting of partial convexity. A partially convex set is a set that is convex in a designated set of convex variables when the others are held…

Functional Analysis · Mathematics 2026-05-06 Tea Štrekelj

In this work, we generalize the probability simplex constraint to matrices, i.e., $\mathbf{X}_1 + \mathbf{X}_2 + \ldots + \mathbf{X}_K = \mathbf{I}$, where $\mathbf{X}_i \succeq 0$ is a symmetric positive semidefinite matrix of size…

Optimization and Control · Mathematics 2020-11-18 Bamdev Mishra , Hiroyuki Kasai , Pratik Jawanpuria

We show that the strongly symmetric spectral convex compact sets are precisely the normalized state spaces of finite-dimensional simple Euclidean Jordan algebras and the simplices. Spectrality is the property that every state has a convex…

Mathematical Physics · Physics 2019-04-09 Howard Barnum , Joachim Hilgert

To a generalized tight continuous frame in a Hilbert space $\H$ indexed by a locally compact space $\Si$ endowed with a Radon measure, one associates a coorbit theory converting spaces of functions on $\Si$ in spaces of vectors comparable…

Functional Analysis · Mathematics 2014-06-30 M. Mantoiu , D. Parra

One of the aims of this paper is to solve an open problem of Lovasz about relations between graph spectra and cut-distance. The paper starts with several inequalities between two versions of the cut-norm and the two largest singular values…

Functional Analysis · Mathematics 2009-12-03 Vladimir Nikiforov

In this paper we obtain a generalization of Matkowski's fixed point theorem and Istratescu's fixed point theorem concerning convex contractions in the framework of b-metric spaces. By providing appropriate examples we show that the above…

Classical Analysis and ODEs · Mathematics 2015-12-17 Radu Miculescu , Alexandru Mihail

Within the framework of the discrete Wess-Zumino-Novikov-Witten theory we analyze the structure of vertex operators on a lattice. In particular, the lattice analogues of operator product expansions and braid relations are discussed. As the…

q-alg · Mathematics 2009-10-30 A. G. Bytsko , V. Schomerus

Computing eigenvalues of very large matrices is a critical task in many machine learning applications, including the evaluation of log-determinants, the trace of matrix functions, and other important metrics. As datasets continue to grow in…

Machine Learning · Statistics 2025-06-16 Siavash Ameli , Chris van der Heide , Liam Hodgkinson , Michael W. Mahoney