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This paper is concerned with a priori error estimates for the local incremental minimization scheme, which is an implicit time discretization method for the approximation of rate-independent systems with non-convex energies. We first show…

Numerical Analysis · Mathematics 2021-05-03 Christian Meyer , Michael Sievers

This paper examines the problem of state estimation in power distribution systems under low-observability conditions. The recently proposed constrained matrix completion method which combines the standard matrix completion method and power…

Optimization and Control · Mathematics 2020-06-09 Yajing Liu , April Sagan , Andrey Bernstein , Rui Yang , Xinyang Zhou , Yingchen Zhang

We present a sampling strategy suitable for optimization problems characterized by high-dimensional design spaces and noisy outputs. Such outputs can arise, for example, in time-averaged objectives that depend on chaotic states. The…

Optimization and Control · Mathematics 2015-05-21 Jason Hicken , Anthony Ashley

For the first time we introduce an error estimator for the numerical approximation of the equations describing the dynamics of sea ice. The idea of the estimator is to identify different error contributions coming from spatial and temporal…

Numerical Analysis · Mathematics 2020-08-11 Carolin Mehlmann , Thomas Richter

Prior work on computable defect-based local error estimators for (linear) time-reversible integrators is extended to nonlinear and nonautonomous evolution equations. We prove that the asymptotic results from the linear case [W. Auzinger and…

Numerical Analysis · Mathematics 2019-01-03 Winfried Auzinger , Harald Hofstätter , Othmar Koch

We present the construction of an exponentially accurate time-dependent Born-Oppenheimer approximation for molecular quantum mechanics. We study molecular systems whose electron masses are held fixed and whose nuclear masses are…

Mathematical Physics · Physics 2009-10-31 George A. Hagedorn , Alain Joye

Distributed algorithms for solving additive or consensus optimization problems commonly rely on first-order or proximal splitting methods. These algorithms generally come with restrictive assumptions and at best enjoy a linear convergence…

Optimization and Control · Mathematics 2017-05-11 Sina Khoshfetrat Pakazad , Christian A. Naesseth , Fredrik Lindsten , Anders Hansson

We consider the unilateral contact problem between an elastic body and a rigid foundation in a description that includes both Tresca and Coulomb friction conditions. For this problem, we present an a posteriori error analysis based on an…

Numerical Analysis · Mathematics 2024-01-08 Ilaria Fontana , Daniele A. Di Pietro

We propose an analysis for the stabilized finite element methods proposed in, E. Burman, Stabilized finite element methods for nonsymmetric, noncoercive, and ill-posed problems. Part I: Elliptic equations. SIAM J. Sci. Comput., 35(6) 2013,…

Numerical Analysis · Mathematics 2014-06-18 Erik Burman

Parametric stochastic simulators are ubiquitous in science, often featuring high-dimensional input parameters and/or an intractable likelihood. Performing Bayesian parameter inference in this context can be challenging. We present a neural…

Machine Learning · Statistics 2021-10-27 Benjamin Kurt Miller , Alex Cole , Patrick Forré , Gilles Louppe , Christoph Weniger

We study deterministic optimal control problems for differential games with finite horizon. We propose new approximations of the strategies in feedback form, and show error estimates and a convergence result of the value in some weak sense…

Optimization and Control · Mathematics 2024-09-04 Olivier Bokanowski , Xavier Warin

A new numerical treatment in the Crank-Nicholson method with the imaginary time evolution operator is presented in order to solve the Schr\"{o}dinger equation. The original time evolution technique is extended to a new operator that…

Computational Physics · Physics 2008-11-26 Daekyoung Kang , E. Won

In this paper a spline based integral approximation is utilized to propose a sequence of approximations to the error function that converge at a significantly faster manner than the default Taylor series. The approximations can be improved…

General Mathematics · Mathematics 2022-07-27 Roy M. Howard

In standard balanced truncation model order reduction, the initial condition is typically ignored in the reduction procedure and is assumed to be zero instead. However, such a reduced-order model may be a bad approximation to the full-order…

Systems and Control · Electrical Eng. & Systems 2022-03-16 Christian Schröder , Matthias Voigt

The Krylov subspace method is a standard approach to approximate quantum evolution, allowing to treat systems with large Hilbert spaces. Although its application is general, and suitable for many-body systems, estimation of the committed…

Quantum Physics · Physics 2021-07-22 Julian Ruffinelli , Emiliano Fortes , Martín Larocca , Diego A. Wisniacki

We propose new local error estimators for splitting and composition methods. They are based on the construction of lower order schemes obtained at each step as a linear combination of the intermediate stages of the integrator, so that the…

Numerical Analysis · Mathematics 2019-10-29 Sergio Blanes , Fernando Casas , Mechthild Thalhammer

We consider hyperelastic problems and their numerical solution using a conforming finite element discretization and iterative linearization algorithms. For these problems, we present equilibrated, weakly symmetric, $H(\rm{div)}$-conforming…

Numerical Analysis · Mathematics 2017-10-19 Michele Botti , Rita Riedlbeck

In this paper we study simulation based optimization algorithms for solving discrete time optimal stopping problems. This type of algorithms became popular among practioneers working in the area of quantitative finance. Using large…

Optimization and Control · Mathematics 2009-09-22 Denis Belomestny

In this work, we consider a rational approximation of the exponential function to design an algorithm for computing matrix exponential in the Hermitian case. Using partial fraction decomposition, we obtain a parallelizable method, where the…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-30 Frédéric Hecht , Sidi-Mahmoud Kaber , Lucas Perrin , Alain Plagne , Julien Salomon

Besides the well-known effect of autocorrelations in time series of Monte Carlo simulation data resulting from the underlying Markov process, using the same data pool for computing various estimates entails additional cross correlations.…

Statistical Mechanics · Physics 2014-11-20 Martin Weigel , Wolfhard Janke
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