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Related papers: Certifying numerical estimates of spectral gaps

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The technique of semidefinite programming (SDP) relaxation can be used to obtain a nontrivial bound on the optimal value of a nonconvex quadratically constrained quadratic program (QCQP). We explore concave quadratic inequalities that hold…

Optimization and Control · Mathematics 2016-09-30 Jaehyun Park , Stephen Boyd

We study $L^p$ bounds on spectral projections for the Laplace operator on compact Riemannian manifolds, restricted to small frequency dependent neighborhoods of submanifolds. In particular, if $\lambda$ is a frequency and the size of the…

Analysis of PDEs · Mathematics 2016-05-17 Katya Krupchyk

An extended two-hadron operator is developed to extract the spectra of irreducible representations (irreps) in the finite volume. The irreps of the group for the finite volume system are projected using a coordinate-space operator. The…

High Energy Physics - Lattice · Physics 2022-05-04 Jia-Jun Wu , Waseem Kamleh , Derek B. Leinweber , Yan Li , Gerrit Schierholz , Ross D. Young , James M. Zanotti

In this article we show the rough outline of a computer algorithm to generate lower bounds on the exponential function of (in principle) arbitrary precision. We implemented this to generate all necessary analytic terms for the Boltzmann…

Numerical Analysis · Computer Science 2013-01-07 Martijn Leisink , Hilbert Kappen

The research on spectral inequalities for discrete Schrodinger Operators has proved fruitful in the last decade. Indeed, several authors analysed the operator's canonical relation to a tridiagonal Jacobi matrix operator. In this paper, we…

Functional Analysis · Mathematics 2013-12-09 Arman Sahovic

Let $\Gamma$ be a discrete finitely presented group. Pick any system $S$ of generators in $\Gamma$. In Cayley graph $\mathrm{Cay}(\Gamma)=\mathrm{Cay}(\Gamma, S)$ with edge set $E$, glue with oriented polygons all the group relations…

Spectral Theory · Mathematics 2025-11-05 Mikhail Dubashinskiy

This article focuses on numerical efficiency of projection algorithms for solving linear optimization problems. The theoretical foundation for this approach is provided by the basic result that bounded finite dimensional linear optimization…

Optimization and Control · Mathematics 2023-09-08 Evgeni Nurminski , Roman Tarasov

This paper is devoted to the theoretical and numerical investigation of an augmented Lagrangian method for the solution of optimization problems with geometric constraints. Specifically, we study situations where parts of the constraints…

Optimization and Control · Mathematics 2022-04-20 Xiaoxi Jia , Christian Kanzow , Patrick Mehlitz , Gerd Wachsmuth

It is known (E.L. Green (1997), O. Post (2003)) that for an arbitrary $m\in\mathbb{N}$ one can construct a periodic non-compact Riemannian manifold $M$ with at least $m$ gaps in the spectrum of the corresponding Laplace-Beltrami operator…

Spectral Theory · Mathematics 2011-11-01 Andrii Khrabustovskyi

We prove tight H\"olderian error bounds for all $p$-cones. Surprisingly, the exponents differ in several ways from those that have been previously conjectured; moreover, they illuminate $p$-cones as a curious example of a class of objects…

Optimization and Control · Mathematics 2024-03-29 Scott B. Lindstrom , Bruno F. Lourenço , Ting Kei Pong

This paper is part of the radial asymptotic stability analysis of the ground state soliton for either the cubic nonlinear Schrodinger or Klein-Gordon equations in three dimensions. We demonstrate by a rigorous method that the linearized…

Analysis of PDEs · Mathematics 2015-05-28 Ovidiu Costin , Min Huang , Wilhelm Schlag

We establish a spectral gap for resonances of the Laplacian of random Schottky surfaces, which is optimal according to a conjecture of Jakobson and Naud.

Spectral Theory · Mathematics 2024-08-01 Irving Calderón , Michael Magee , Frédéric Naud

In this paper, we give some lower bounds for several eigenvalues. Firstly, we investigate the eigenvalues $\lambda_i$ of the Laplace operator and prove a sharp lower bound. Moreover, we extent this estimate of the eigenvalues to general…

Differential Geometry · Mathematics 2020-11-26 Zhengchao Ji , Hongwei Xu

We prove an O(log n) bound for the expectation of the logarithm of the condition number K for the computation of optimizers of linear programs.

Optimization and Control · Mathematics 2011-05-12 Dennis Cheung , Felipe Cucker

In this paper we present some spectral property for quotient bounded operators and locally bounded operators on locally convex spaces. We introduce the spectral radius of a quotient bounded operator and we show that the Gelfand formula for…

Functional Analysis · Mathematics 2007-05-23 Mirel Sorin Stoian

In this work, we show how to parameterize a density matrix that has an arbitrary symmetry, knowing the generators of the Lie algebra (if the symmetry group is a connected Lie group) or the generators of its underlying group (in case it is…

Quantum Physics · Physics 2023-01-25 Inés Corte , Marcelo Losada , Diego Tielas , Federico Holik , Lorena Rebón

We introduce an abstract framework for the study of clustering in metric graphs: after suitably metrising the space of graph partitions, we restrict Laplacians to the clusters thus arising and use their spectral gaps to define several…

Spectral Theory · Mathematics 2020-05-05 James B. Kennedy , Pavel Kurasov , Corentin Léna , Delio Mugnolo

The main objective of the present work is to study the negative spectrum of (differential) Laplace operators on metric graphs as well as their resolvents and associated heat semigroups. We prove an upper bound on the number of negative…

Mathematical Physics · Physics 2007-05-23 Vadim Kostrykin , Robert Schrader

We introduce a new quantum algorithm for computing the Betti numbers of a simplicial complex. In contrast to previous quantum algorithms that work by estimating the eigenvalues of the combinatorial Laplacian, our algorithm is an instance of…

Quantum Physics · Physics 2023-07-17 Mitchell Black , William Maxwell , Amir Nayyeri

Abstracting neural networks with constraints they impose on their inputs and outputs can be very useful in the analysis of neural network classifiers and to derive optimization-based algorithms for certification of stability and robustness…

Machine Learning · Computer Science 2021-05-04 Navid Hashemi , Justin Ruths , Mahyar Fazlyab
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