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Computing accurate yet efficient approximations to the solutions of the electronic Schr\"odinger equation has been a paramount challenge of computational chemistry for decades. Quantum Monte Carlo methods are a promising avenue of…

Chemical Physics · Physics 2023-09-25 Zeno Schätzle , Bernát Szabó , Matĕj Mezera , Jan Hermann , Frank Noé

In this paper we consider the Cauchy problem for $2m$-order stochastic partial differential equations of parabolic type in a class of stochastic Hoelder spaces. The Hoelder estimates of solutions and their spatial derivatives up to order…

Probability · Mathematics 2019-05-23 Yuxing Wang , Kai Du

We study multivariate integration over the $s$-dimensional unit cube in a weighted space of infinitely differentiable functions. It is known from a recent result by Suzuki that there exists a good quasi-Monte Carlo (QMC) rule which achieves…

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

Averaged operators have played an important role in fixed point theory in Hilbert spaces. They emerged as a necessity to obtain solutions to fixed point problems where the underlying operator is not contractive and thus renders Banach fixed…

Functional Analysis · Mathematics 2025-03-11 Arian Berdellima

This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over…

High Energy Physics - Lattice · Physics 2013-11-20 Andreas Ammon , Tobias Hartung , Karl Jansen , Hernan Leovey , Andreas Griewank , Micheal Müller-Preussker

In the present paper we study quasi-Monte Carlo rules for approximating integrals over the $d$-dimensional unit cube for functions from weighted Sobolev spaces of regularity one. While the properties of these rules are well understood for…

Numerical Analysis · Mathematics 2020-01-17 Peter Kritzer , Friedrich Pillichshammer , G. W. Wasilkowski

Harmonic and polyanalytic functional calculi have been recently defined for bounded commuting operators. Their definitions are based on the Cauchy formula of slice hyperholomorphic functions and on the factorization of the Laplace operator…

Spectral Theory · Mathematics 2023-04-21 Fabrizio Colombo , Antonino De Martino , Stefano Pinton

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

In this paper, we will introduce a high order numerical method to solve the scattering problems with non-periodic incident fields and (locally perturbed) periodic surfaces. For the problems we are considering, the classical methods to treat…

Numerical Analysis · Mathematics 2018-07-26 Ruming Zhang

This article summarises the theory of several bounded functional calculi for unbounded operators that have recently been discovered. The extend the Hille--Phillips calculus for (negative) generators $A$ of certain bounded $C_0$-semigroups,…

Functional Analysis · Mathematics 2022-02-08 Charles Batty , Alexander Gomilko , Yuri Tomilov

We study higher-order weighted Dirichlet-type spaces on the unit disc associated with a class of poly-superharmonic weights. A higher-order Littlewood Paley formula is established enabling the computation of higher-order weighted Dirichlet…

Functional Analysis · Mathematics 2026-04-24 Ashish Kujur , Md. Ramiz Reza

This paper proposes a new importance sampling (IS) that is tailored to quasi-Monte Carlo (QMC) integration over $\mathbb{R}^s$. IS introduces a multiplicative adjustment to the integrand by compensating the sampling from the proposal…

Numerical Analysis · Mathematics 2025-09-19 Zexin Pan , Du Ouyang , Zhijian He

The radial basis function (RBF) and quasi Monte Carlo (QMC) methods are two very promising schemes to handle high-dimension problems with complex and moving boundary geometry due to the fact that they are independent of dimensionality and…

Numerical Analysis · Mathematics 2025-10-20 W. Chen , J. He

In this paper, the sharp quantitative weighted bounds for the iterated commutators of a class of multilinear operators were systematically studied. This class of operators contains multilinear Calder\'{o}n-Zygmund operators, multilinear…

Classical Analysis and ODEs · Mathematics 2024-01-04 Jiawei Tan , Qingying Xue

The Rational Hybrid Monte Carlo (RHMC) algorithm extends the Hybrid Monte Carlo algorithm for lattice QCD simulations to situations involving fractional powers of the determinant of the quadratic Dirac operator. This avoids the updating…

High Energy Physics - Lattice · Physics 2008-11-26 J. B. Kogut , D. K. Sinclair

We extend the theory of regularity structures [Hai14] to allow processes belonging to locally $m$-convex topological algebras. This extension includes processes in the locally $C^{*}$-algebras of [CHP25] used to localise singular stochastic…

Probability · Mathematics 2025-09-11 Ajay Chandra , Martin Hairer , Martin Peev

This work introduces an end-to-end framework for multi-asset option pricing that combines market-consistent risk-neutral density recovery with quantum-accelerated numerical integration. We first calibrate arbitrage-free marginal…

Computational Finance · Quantitative Finance 2026-01-08 Julien Hok , Álvaro Leitao

We study quasi-Monte Carlo integration for twice differentiable functions defined over a triangle. We provide an explicit construction of infinite sequences of points including one by Basu and Owen (2015) as a special case, which achieves…

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

In this paper, we consider Quasi-Monte Carlo (QMC) worst case error of weighted smooth function classes in $C^\infty[0,1]^s$ by a digital net over $\mathbb F_2$. We show that the ratio of the worst case error to the QMC integration error of…

Numerical Analysis · Mathematics 2016-11-03 Matsumoto Makoto , Ryuichi Ohori , Takehito Yoshiki

Many machine learning problems involve Monte Carlo gradient estimators. As a prominent example, we focus on Monte Carlo variational inference (MCVI) in this paper. The performance of MCVI crucially depends on the variance of its stochastic…

Machine Learning · Statistics 2018-07-05 Alexander Buchholz , Florian Wenzel , Stephan Mandt