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This article investigates the approximation quality achievable for biobjective minimization problems with respect to the Pareto cone by solutions that are (approximately) optimal with respect to larger ordering cones. When simultaneously…

Optimization and Control · Mathematics 2021-09-22 Arne Herzel , Stephan Helfrich , Stefan Ruzika , Clemens Thielen

For the pure biharmonic equation and a biharmonic singular perturbation problem, a residual-based error estimator is introduced which applies to many existing nonconforming finite elements. The error estimator involves the local…

Numerical Analysis · Mathematics 2024-10-18 Dietmar Gallistl , Shudan Tian

We present a new optimization-based method for atomistic-to-continuum (AtC) coupling. The main idea is to cast the coupling of the atomistic and continuum models as a constrained optimization problem with virtual Dirichlet controls on the…

Numerical Analysis · Mathematics 2013-04-19 Derek Olson , Pavel Bochev , Mitchell Luskin , Alexander V. Shapeev

We study a cutting-plane method for semidefinite optimization problems (SDOs), and supply a proof of the method's convergence, under a boundedness assumption. By relating the method's rate of convergence to an initial outer approximation's…

Optimization and Control · Mathematics 2020-02-17 Dimitris Bertsimas , Ryan Cory-Wright

We prove optimal bounds for the convergence rate of ordinal embedding (also known as non-metric multidimensional scaling) in the 1-dimensional case. The examples witnessing optimality of our bounds arise from a result in additive number…

Statistics Theory · Mathematics 2019-05-01 Jordan S. Ellenberg , Lalit Jain

Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration…

Optimization and Control · Mathematics 2019-01-25 Ching-pei Lee , Stephen J. Wright

This paper introduces a new computational methodology for determining a-posteriori multi-objective error estimates for finite-element approximations, and for constructing corresponding (quasi-)optimal adaptive refinements of finite-element…

Numerical Analysis · Mathematics 2016-11-23 E. H. van Brummelen , S. Zhuk , G. J. van Zwieten

We formulate an energy-based atomistic-to-continuum coupling method based on blending the quasicontinuum method for the simulation of crystal defects. We utilize theoretical results from Ortner and Van Koten (manuscript) to derive optimal…

Numerical Analysis · Mathematics 2012-09-06 M. Luskin , C. Ortner , B. Van Koten

In [19], a general, inexact, efficient proximal quasi-Newton algorithm for composite optimization problems has been proposed and a sublinear global convergence rate has been established. In this paper, we analyze the convergence properties…

Numerical Analysis · Computer Science 2017-10-18 Hiva Ghanbari , Katya Scheinberg

We study the properties of a quasi-one dimensional superconductor which consists of an alternating array of two inequivalent chains. This model is a simple charicature of a locally striped high temperature superconductor, and is more…

Superconductivity · Physics 2009-10-31 M. Granath , V. Oganesyan , S. A. Kivelson , E. Fradkin , V. J. Emery

In this paper, we study a priori error estimates for the finite element approximation of the nonlinear Schr\"{o}dinger-Poisson model. The electron density is defined by an infinite series over all eigenvalues of the Hamiltonian operator. To…

Numerical Analysis · Mathematics 2023-07-20 Tao Cui , Wenhao Lu , Naiyan Pan , Weiying Zheng

Variational inequalities represent a broad class of problems, including minimization and min-max problems, commonly found in machine learning. Existing second-order and high-order methods for variational inequalities require precise…

We analyze a force-based quasicontinuum approximation to a one-dimensional system of atoms that interact by a classical atomistic potential. This force-based quasicontinuum approximation is derived as the modification of an energy-based…

Numerical Analysis · Mathematics 2010-07-19 Matthew Dobson , Mitchell Luskin

In an order-of-addition experiment, each treatment is a permutation of m components. It is often unaffordable to test all the m! treatments, and the design problem arises. We consider a model that incorporates the order of each pair of…

Statistics Theory · Mathematics 2018-05-15 Jiayu Peng , Rahul Mukerjee , Dennis K. J. Lin

The problems of optimally estimating a phase, a direction, and the orientation of a Cartesian frame (or trihedron) with general pure states are addressed. Special emphasis is put on estimation schemes that allow for inconclusive answers or…

Quantum Physics · Physics 2013-08-09 B. Gendra , E. Ronco-Bonvehi , J. Calsamiglia , R. Muñoz-Tapia , E. Bagan

First-order methods for minimization and saddle point (min-max) problems are widely used for solving large-scale problems, in particular arising in machine learning. The majority of works obtain favorable complexity guarantees of such…

Simulating quantum dynamics beyond the reach of classical computers is one of the main envisioned applications of quantum computers. The most promising quantum algorithms to this end in the near-term are the simplest, which use the Trotter…

Quantum Physics · Physics 2022-05-25 David Layden

Artificial quasicrystals are nowadays routinely manufactured, yet only two naturally occurring examples are known. We present a class of systems with the potential to be realized both artificially and in nature, in which the lowest energy…

Strongly Correlated Electrons · Physics 2015-12-07 Felix Flicker , Jasper van Wezel

For a next-nearest neighbour pair interaction model in a periodic domain, a priori and a posteriori analyses of the quasinonlocal quasicontinuum method (QNL-QC) are presented. The results are valid for large deformations and essentially…

Numerical Analysis · Mathematics 2009-11-06 C. Ortner

In dynamical system theory, the process of obtaining a reduced-order approximation of the high-order model is called model order reduction. The closeness of the reduced-order model to the original model is generally gauged by using system…

Systems and Control · Electrical Eng. & Systems 2023-03-07 Umair Zulfiqar , Xin Dua , Qiuyan Song , Muwahida Liaquat , Victor Sreeram