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We develop a mesh-free, derivative-free, matrix-free, and highly parallel localized stochastic method for high-dimensional semilinear parabolic PDEs. The efficiency of the proposed method is built upon four essential components: (i) a…

Numerical Analysis · Mathematics 2025-10-14 Shuixin Fang , Changtao Sheng , Bihao Su , Tao Zhou

In this paper we investigate a priori error estimates for the space-time Galerkin finite element discretization of an optimal control problem governed by a simplified linear gradient enhanced damage model. The model equations are of a…

Numerical Analysis · Mathematics 2020-04-10 Marita Holtmannspötter , Arnd Rösch , Boris Vexler

A transient magneto-quasistatic vector potential formulation involving nonlinear material is spatially discretized using the finite element method of first and second polynomial order. By applying a generalized Schur complement the…

Computational Engineering, Finance, and Science · Computer Science 2020-11-09 Bernhard Kähne , Markus Clemens , Sebastian Schöps

The projection formalism for calculating effective Hamiltonians and resonances is generalized to the nonlocal and/or nonhermitian case, so that it is applicable to the reduction of relativistic systems (Bethe-Salpeter equations), and to…

High Energy Physics - Theory · Physics 2007-05-23 Arnold Neumaier

In this paper we show how to accelerate randomized coordinate descent methods and achieve faster convergence rates without paying per-iteration costs in asymptotic running time. In particular, we show how to generalize and efficiently…

Data Structures and Algorithms · Computer Science 2013-05-09 Yin Tat Lee , Aaron Sidford

This paper addresses the numerical implementation of the transparent boundary condition (TBC) and its various approximations for the free Schr\"odinger equation on a rectangular computational domain. In particular, we consider the exact TBC…

Numerical Analysis · Mathematics 2024-05-28 Samardhi Yadav , Vishal Vaibhav

We present the first mathematical analysis of stochastic density functional theory (DFT) in the context of the Hartree approximation. We motivate our analysis via the notion of nearly-optimal or $\tilde{O}(n)$ scaling with respect to the…

Numerical Analysis · Mathematics 2025-06-03 Yuhang Cai , Michael Lindsey

In calculating integral or discrete transforms, use has been made of fast algorithms for multiplying vectors by matrices whose elements are specified as values of special (Chebyshev, Legendre, Laguerre, etc.) functions. The currently…

Numerical Analysis · Mathematics 2022-08-11 Andrew V. Terekhov

Based on the Hermite expansion of the distribution function, we introduce a Galerkin spectral method for the spatially homogeneous Boltzmann equation with the realistic inverse-power-law models. A practical algorithm is proposed to evaluate…

Numerical Analysis · Mathematics 2019-09-04 Yanli Wang , Zhenning Cai

We introduce a simple and stable computational method for ill-posed partial differential equation (PDE) problems. The method is based on Schr\"odingerization, introduced in [S. Jin, N. Liu and Y. Yu, arXiv:2212.13969][S. Jin, N. Liu and Y.…

Numerical Analysis · Mathematics 2024-11-11 Shi Jin , Nana Liu , Chuwen Ma

We present an algorithmic framework for matrix-free evaluation of discontinuous Galerkin finite element operators based on sum factorization on quadrilateral and hexahedral meshes. We identify a set of kernels for fast quadrature on cells…

Mathematical Software · Computer Science 2019-09-11 Martin Kronbichler , Katharina Kormann

In this work, we consider the approximation of parametric maps using the so-called Galerkin POD-NN method. This technique combines the computation of a reduced basis via proper orthogonal decomposition (POD) and artificial neural networks…

Numerical Analysis · Mathematics 2025-10-31 Jürgen Dölz , Fernando Henríquez

In this work we revisit the arithmetic and bit complexity of Hermitian eigenproblems. Recently, [BGVKS, FOCS 2020] proved that a (non-Hermitian) matrix can be diagonalized with a randomized algorithm in $O(n^{\omega}\log^2(n/\epsilon))$…

Data Structures and Algorithms · Computer Science 2025-04-29 Aleksandros Sobczyk

The Hilbert Schmidt Independence Criterion (HSIC) is a kernel dependence measure that has applications in various aspects of machine learning. Conveniently, the objectives of different dimensionality reduction applications using HSIC often…

Machine Learning · Statistics 2019-09-12 Chieh Wu , Jared Miller , Yale Chang , Mario Sznaier , Jennifer Dy

Quantum computers are known for their potential to achieve up-to-exponential speedup compared to classical computers for certain problems. To exploit the advantages of quantum computers, we propose quantum algorithms for linear stochastic…

Quantum Physics · Physics 2025-06-26 Shi Jin , Nana Liu , Wei Wei

An implicit purification scheme is proposed for calculation of the temperature-dependent, grand canonical single-particle density matrix, given as a Fermi operator expansion in terms of the Hamiltonian. The computational complexity is shown…

Materials Science · Physics 2009-11-10 Anders M. N. Niklasson

The numerical simulation of the time-dependent Schr\"odinger equation for quantum systems is a very active research topic. Yet, resolving the solution sufficiently in space and time is challenging and mandates the use of modern…

Numerical Analysis · Mathematics 2020-06-11 Hannah Rittich , Robert Speck

We propose an adaptive Hermite spectral method for the Vlasov-Poisson system based on a recently developed frequency indicator that measures the contribution of the high-order expansion coefficients. Precisely, the symmetrically weighted…

Numerical Analysis · Mathematics 2026-05-19 Sihong Shao , Yanli Wang , Jie Wu

We consider the problem of constructing transparent boundary conditions for the time-dependent Schr\"odinger equation with a compactly supported binding potential and, if desired, a spatially uniform, time-dependent electromagnetic vector…

Numerical Analysis · Mathematics 2019-07-08 Jason Kaye , Leslie Greengard

We consider the optimization problem of the form $\min_{x \in \mathbb{R}^d} f(x) \triangleq \mathbb{E}_{\xi} [F(x; \xi)]$, where the component $F(x;\xi)$ is $L$-mean-squared Lipschitz but possibly nonconvex and nonsmooth. The recently…

Optimization and Control · Mathematics 2024-05-15 Lesi Chen , Jing Xu , Luo Luo