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The component-by-component construction is the standard method of finding good lattice rules or polynomial lattice rules for numerical integration. Several authors have reported that in numerical experiments the generating vector sometimes…

Numerical Analysis · Mathematics 2015-06-29 Josef Dick , Peter Kritzer

The search for multivariate quadrature rules of minimal size with a specified polynomial accuracy has been the topic of many years of research. Finding such a rule allows accurate integration of moments, which play a central role in many…

Numerical Analysis · Mathematics 2021-05-04 John D. Jakeman , Akil Narayan

This paper investigates the construction of space-filling designs for computer experiments. The space-filling property is characterized by the covering and separation radii of a design, which are integrated through the unified criterion of…

Methodology · Statistics 2026-02-18 Naoki Sakai , Takashi Goda

In this paper, we study the approximation of $d$-dimensional $\rho$-weighted integrals over unbounded domains $\mathbb{R}_+^d$ or $\mathbb{R}^d$ using a special change of variables, so that quasi-Monte Carlo (QMC) or sparse grid rules can…

Numerical Analysis · Mathematics 2018-12-12 Peter Kritzer , Friedrich Pillichshammer , Leszek Plaskota , G. W. Wasilkowski

Quasi-Monte Carlo (QMC) is an essential tool for integral approximation, Bayesian inference, and sampling for simulation in science, etc. In the QMC area, the rank-1 lattice is important due to its simple operation, and nice properties for…

Computation · Statistics 2020-11-13 Yueming Lyu , Yuan Yuan , Ivor W. Tsang

We propose a new method to construct maximin distance designs with arbitrary number of dimensions and points. The proposed designs hold interleaved-layer structures and are by far the best maximin distance designs in four or more…

Methodology · Statistics 2018-07-09 Xu He

We present a polynomial hybrid Monte Carlo (PHMC) algorithm for lattice QCD with odd numbers of flavors of O(a)-improved Wilson quark action. The algorithm makes use of the non-Hermitian Chebyshev polynomial to approximate the inverse…

We investigate quasi-Monte Carlo (QMC) integration over the $s$-dimensional unit cube based on rank-1 lattice point sets in weighted non-periodic Sobolev spaces $\mathcal{H}(K_{\alpha,\boldsymbol{\gamma},s}^{\mathrm{sob}})$ and their…

Numerical Analysis · Mathematics 2019-12-09 Takashi Goda , Kosuke Suzuki , Takehito Yoshiki

We study the feature-scaled version of the Monte Carlo algorithm with linear function approximation. This algorithm converges to a scale-invariant solution, which is not unduly affected by states having feature vectors with large norms. The…

Machine Learning · Computer Science 2022-05-31 Rahul Madhavan , Hemanta Makwana

Quasi-Monte Carlo methods are used for numerically integrating multivariate functions. However, the error bounds for these methods typically rely on a priori knowledge of some semi-norm of the integrand, not on the sampled function values.…

Numerical Analysis · Mathematics 2015-10-27 Lluís Antoni Jiménez Rugama , Fred J. Hickernell

We present a systematic computational framework for generating positive quadrature rules in multiple dimensions on general geometries. A direct moment-matching formulation that enforces exact integration on polynomial subspaces yields…

Numerical Analysis · Computer Science 2018-09-03 Vahid Keshavarzzadeh , Robert M. Kirby , Akil Narayan

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

In this paper, we study an efficient algorithm for constructing point sets underlying quasi-Monte Carlo integration rules for weighted Korobov classes. The algorithm presented is a reduced fast component-by-component digit-by-digit…

Numerical Analysis · Mathematics 2022-11-23 Peter Kritzer , Onyekachi Osisiogu

Estimating the trace of the inverse of a large matrix is an important problem in lattice quantum chromodynamics. A multilevel Monte Carlo method is proposed for this problem that uses different degree polynomials for the levels. The…

High Energy Physics - Lattice · Physics 2023-06-19 Paul Lashomb , Ronald B. Morgan , Travis Whyte , Walter Wilcox

We study the approximation of integrals $\int_D f(\boldsymbol{x}^\top A) \mathrm{d} \mu(\boldsymbol{x})$, where $A$ is a matrix, by quasi-Monte Carlo (QMC) rules $N^{-1} \sum_{k=0}^{N-1} f(\boldsymbol{x}_k^\top A)$. We are interested in…

Numerical Analysis · Mathematics 2023-05-22 Josef Dick , Adrian Ebert , Lukas Herrmann , Peter Kritzer , Marcello Longo

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

The study further explores randomized QMC (RQMC), which maintains the QMC convergence rate and facilitates computational efficiency analysis. Emphasis is laid on integrating randomly shifted lattice rules, a distinct RQMC quadrature, with…

Numerical Analysis · Mathematics 2023-09-21 Zhan Zheng , Hejin Wang , Xiaoqun Wang

In the random case setting, scrambled polynomial lattice rules as discussed in \cite{BD10} enjoy more favourable strong tractablility properties than scrambled digital nets. This short note discusses the application of scrambled polynomial…

Numerical Analysis · Mathematics 2010-11-01 Jan Baldeaux

In lattice Quantum Field Theory, we are often presented with integrals over polynomials of coefficients of matrices in U(N) or SU(N) with respect to the Haar measure. In some physical situations, e.g., in presence of a chemical potential,…

High Energy Physics - Lattice · Physics 2016-10-07 Andreas Ammon , Tobias Hartung , Karl Jansen , Hernan Leövey , Julia Volmer

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