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We discuss an algorithm for Tchakaloff-like compression of Quasi-MonteCarlo (QMC) volume/surface integration on union of balls (multibubbles). The key tools are Davis-Wilhelmsen theorem on the so-called Tchakaloff sets for positive linear…

Numerical Analysis · Mathematics 2023-03-03 Giacomo Elefante , Alvise Sommariva , Marco Vianello

Quasi-Monte Carlo (QMC) methods are being adopted in statistical applications due to the increasingly challenging nature of numerical integrals that are now routinely encountered. For integrands with $d$-dimensions and derivatives of order…

Computation · Statistics 2016-04-04 Chris. J. Oates , Mark Girolami

We study quasi-Monte Carlo (QMC) integration over the multi-dimensional unit cube in several weighted function spaces with different smoothness classes. We consider approximating the integral of a function by the median of several integral…

Numerical Analysis · Mathematics 2024-02-20 Takashi Goda , Kosuke Suzuki , Makoto Matsumoto

We present a brief survey on the compression of discrete measures by Caratheodory-Tchakaloff Subsampling, its implementation by Linear or Quadratic Programming and the application to multivariate polynomial Least Squares. We also give an…

Numerical Analysis · Mathematics 2016-11-18 Federico Piazzon , Alvise Sommariva , Marco Vianello

Quasi-Monte Carlo (QMC) methods are equal weight quadrature rules to approximate integrals over the unit cube with respect to the uniform measure. In this paper we discuss QMC integration with respect to general product measures defined on…

Numerical Analysis · Mathematics 2020-09-16 Josef Dick , Friedrich Pillichshammer

A compression algorithm is introduced for multi-determinant wave functions which can greatly reduce the number of determinants that need to be evaluated in quantum Monte Carlo calculations. We have devised an algorithm with three levels of…

Computational Physics · Physics 2015-06-17 Gihan L. Weerasinghe , Pablo Lopez Rios , Richard J. Needs

We analyze the convergence of higher order Quasi-Monte Carlo (QMC) quadratures of solution-functionals to countably-parametric, nonlinear operator equations with distributed uncertain parameters taking values in a separable Banach space $X$…

Numerical Analysis · Mathematics 2015-06-25 Josef Dick , Quoc T. Le Gia , Christoph Schwab

We apply the Quasi Monte Carlo (QMC) and recursive numerical integration methods to evaluate the Euclidean, discretized time path-integral for the quantum mechanical anharmonic oscillator and a topological quantum mechanical rotor model.…

High Energy Physics - Lattice · Physics 2016-01-26 A. Ammon , A. Genz , T. Hartung , K. Jansen , H. Leövey , J. Volmer

In the present paper, an integrated paradigm for topology optimization on complex surfaces with arbitrary genus is proposed. The approach is constructed based on the two-dimensional (2D) Moving Morphable Component (MMC) framework, where a…

Optimization and Control · Mathematics 2022-02-03 Wendong Huo , Chang Liu , Zongliang Du , Xudong Jiang , Zhengyu Liu , Xu Guo

We propose a new formulation for integrating over smooth curves and surfaces that are described by their closest point mappings. Our method is designed for curves and surfaces that are not defined by any explicit parameterization and is…

Numerical Analysis · Mathematics 2015-10-16 Catherine Kublik , Richard Tsai

This article provides an overview of some interfaces between the theory of quasi-Monte Carlo (QMC) methods and applications. We summarize three QMC theoretical settings: first order QMC methods in the unit cube $[0,1]^s$ and in…

Numerical Analysis · Mathematics 2017-10-30 Frances Y. Kuo , Dirk Nuyens

We establish the following uniformization result for metric spaces $X$ of finite Hausdorff 2-measure. If $X$ is homeomorphic to a smooth 2-manifold $M$ with non-empty boundary, then we show that $X$ admits a quasiconformal almost…

Metric Geometry · Mathematics 2022-08-25 Damaris Meier

Subdivision surfaces provide an elegant isogeometric analysis framework for geometric design and analysis of partial differential equations defined on surfaces. They are already a standard in high-end computer animation and graphics and are…

Numerical Analysis · Mathematics 2018-06-04 Qiaoling Zhang , Malcolm Sabin , Fehmi Cirak

Matrix factorization is a popular framework for modeling low-rank data matrices. Motivated by manifold learning problems, this paper proposes a quadratic matrix factorization (QMF) framework to learn the curved manifold on which the dataset…

Machine Learning · Computer Science 2023-01-31 Zheng Zhai , Hengchao Chen , Qiang Sun

Quasi-Monte Carlo algorithms are studied for designing discrete approximations of two-stage linear stochastic programs. Their integrands are piecewise linear, but neither smooth nor lie in the function spaces considered for QMC error…

Optimization and Control · Mathematics 2014-10-31 H. Heitsch , H. Leövey , W. Römisch

Quasi-Monte Carlo (QMC) is a powerful method for evaluating high-dimensional integrals. However, its use is typically limited to distributions where direct sampling is straightforward, such as the uniform distribution on the unit hypercube…

Numerical Analysis · Mathematics 2024-12-24 Sifan Liu

We consider a parametric convex quadratic programming, CQP, relaxation for the quadratic knapsack problem, QKP. This relaxation maintains partial quadratic information from the original QKP by perturbing the objective function to obtain a…

Optimization and Control · Mathematics 2019-06-11 Marcia Fampa , Daniela Cristina Lubke , Fei Wang , Henry Wolkowicz

In this paper, we study quasi-Monte Carlo (QMC) integration in weighted Sobolev spaces. In contrast to many previous results the QMC algorithms considered here are of open type, i.e., they are extensible in the number of sample points…

Numerical Analysis · Mathematics 2014-11-18 Peter Hellekalek , Peter Kritzer , Friedrich Pillichshammer

In a previous paper (J. Comp. Phys. 230 (2011), 3668--3694), the authors proposed a new practical method for computing expected values of functionals of solutions for certain classes of elliptic partial differential equations with random…

Numerical Analysis · Mathematics 2018-04-03 Ivan G. Graham , Frances Y. Kuo , Dirk Nuyens , Rob Scheichl , Ian H. Sloan

A control in feedback form is derived for linear quadratic, time-invariant optimal control problems subject to parabolic partial differential equations with coefficients depending on a countably infinite number of uncertain parameters. It…

Optimization and Control · Mathematics 2024-09-25 Philipp A. Guth , Peter Kritzer , Karl Kunisch
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