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Related papers: Halfspaces minimise nonlocal perimeter: a proof vi…

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We provide a holomorphic description of the Hilbert space H(j_1,..,j_n) of SU(2)-invariant tensors (intertwiners) and establish a holomorphically factorized formula for the decomposition of identity in H(j_1,..,j_n). Interestingly, the…

High Energy Physics - Theory · Physics 2015-03-13 Laurent Freidel , Kirill Krasnov , Etera R. Livine

We prove that certain nonlocal functionals defined on partitions made of measurable sets Gamma-converge to a local functional modeled on the perimeter in the sense of De Giorgi. Those nonlocal functionals involve generalized surface tension…

Analysis of PDEs · Mathematics 2025-06-26 Thomas Gabard , Vincent Millot

In this paper we study the free boundary regularity for almost-minimizers of the functional \begin{equation*} J(u)=\int_{\mathcal O} |\nabla u(x)|^2 +q^2_+(x)\chi_{\{u>0\}}(x) +q^2_-(x)\chi_{\{u<0\}}(x)\ dx \end{equation*} where $q_\pm \in…

Analysis of PDEs · Mathematics 2019-05-15 Guy David , Max Engelstein , Tatiana Toro

We confirm a conjecture of Chi Li which says that the minimizer of the normalized volume function for a klt singularity is unique up to rescaling. This is achieved by defining stability thresholds for valuations, and then showing that a…

Algebraic Geometry · Mathematics 2020-05-19 Chenyang Xu , Ziquan Zhuang

We propose a kernel-based nonparametric framework for mean-variance optimization that enables inference on economically motivated shape constraints in finance, including positivity, monotonicity, and convexity. Many central hypotheses in…

Machine Learning · Statistics 2026-01-26 Rohan Sen

We consider the convex optimization problem P: min {f(x): x in K} where "f" is convex continuously differentiable, and K is a compact convex set in Rn with representation {x: g_j(x) >=0, j=1,;;,m} for some continuously differentiable…

Optimization and Control · Mathematics 2014-01-29 Jean-Bernard Lasserre

Based on recent developments in the theory of fractional Sobolev spaces, an interesting new class of nonlocal variational problems has emerged in the literature. These problems, which are the focus of this work, involve integral functionals…

Analysis of PDEs · Mathematics 2021-04-13 Carolin Kreisbeck , Hidde Schönberger

We introduce a notion of fractional perimeter in an abstract Wiener space, and we show that halfspaces are the only volume-constrained minimisers.

Analysis of PDEs · Mathematics 2014-07-22 Matteo Novaga , Diego Pallara , Yannick Sire

In this paper, we prove that nonnegative polyharmonic functions on the upper half space satisfying a conformally invariant nonlinear boundary condition have to be the "\emph{polynomials} plus \emph{bubbles}" form. The nonlinear problem is…

Analysis of PDEs · Mathematics 2016-09-21 Liming Sun , Jingang Xiong

We investigate two new optimization problems -- minimizing a submodular function subject to a submodular lower bound constraint (submodular cover) and maximizing a submodular function subject to a submodular upper bound constraint…

Data Structures and Algorithms · Computer Science 2013-11-12 Rishabh Iyer , Jeff Bilmes

We announce new existence and $\varepsilon$-regularity results for minimisers of the relaxation of strongly quasiconvex integrals that on smooth maps $u\colon\Omega\subset\mathbb{R}^{n}\to\mathbb{R}^{N}$ are defined by $$u\mapsto…

Analysis of PDEs · Mathematics 2019-03-20 Franz Gmeineder , Jan Kristensen

We discuss the notion of optimal polynomial approximants in multivariable reproducing kernel Hilbert spaces. In particular, we analyze difficulties that arise in the multivariable case which are not present in one variable, for example, a…

Complex Variables · Mathematics 2022-05-03 Meredith Sargent , Alan Sola

We introduce a fresh scheme based on the local hidden variable models to quantify nonlocality for arbitrarily high-dimensional quantum systems. Our scheme explores the minimal amount of white noise that must be added to the system in order…

Quantum Physics · Physics 2009-11-09 Dong-Ling Deng , Jing-Ling Chen , Zi-Sui Zhou

We consider the problem of reconstructing an unknown bounded function $u$ defined on a domain $X\subset \mathbb{R}^d$ from noiseless or noisy samples of $u$ at $n$ points $(x^i)_{i=1,\dots,n}$. We measure the reconstruction error in a norm…

Numerical Analysis · Mathematics 2016-08-02 Albert Cohen , Giovanni Migliorati

Quantization in the minisuperspace of non minimal scalar-tensor theories leads to a partial differential equation which is non separable. Through a conformal transformation we can recast the Wheeler-DeWitt equation in an integrable form,…

General Relativity and Quantum Cosmology · Physics 2009-10-31 Julio C. Fabris , Nelson Pinto-Neto , A. F. Velasco

Designing computational experiments involving $\ell_1$ minimization with linear constraints in a finite-dimensional, real-valued space for receiving a sparse solution with a precise number $k$ of nonzero entries is, in general, difficult.…

Optimization and Control · Mathematics 2013-09-11 Christian Kruschel , Dirk A. Lorenz

Functionals that strive to correct for such self-interaction errors, such as those obtained by imposing the Perdew-Zunger self-interaction correction or the generalized Koopmans' condition, become orbital dependent or orbital-density…

Materials Science · Physics 2011-08-30 Cheol-Hwan Park , Andrea Ferretti , Ismaila Dabo , Nicolas Poilvert , Nicola Marzari

Given a positive lower semi-continuous density $f$ on $\mathbb{R}^2$ the weighted volume $V_f:=f\mathscr{L}^2$ is defined on the $\mathscr{L}^2$-measurable sets in $\mathbb{R}^2$. The $f$-weighted perimeter of a set of finite perimeter $E$…

Differential Geometry · Mathematics 2017-09-21 I. McGillivray

In quantum and quantum-inspired machine learning, the very first step is to embed the data in quantum space known as Hilbert space. Developing quantum kernel function (QKF), which defines the distances among the samples in the Hilbert…

Quantum Physics · Physics 2022-08-15 Wei-Ming Li , Shi-Ju Ran

A framework for estimation and hypothesis testing of functional restrictions against general alternatives is proposed. The parameter space is a reproducing kernel Hilbert space (RKHS). The null hypothesis does not necessarily define a…

Methodology · Statistics 2018-08-21 Alessio Sancetta
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