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Many of the new developments in machine learning are connected with gradient-based optimization methods. Recently, these methods have been studied using a variational perspective. This has opened up the possibility of introducing…

Optimization and Control · Mathematics 2024-04-17 Cédric M. Campos , Alejandro Mahillo , David Martín de Diego

We introduce a class of fourth order symplectic algorithms that are ideal for doing long time integration of gravitational few-body problems. These algorithms have only positive time steps, but require computing the force gradient in…

Astrophysics · Physics 2007-05-23 Siu A. Chin , C. R. Chen

We derive and analyze numerical methods for underdamped (kinetic) Langevin dynamics in a domain with elastic reflection at the boundary. First-order approximations are based on an Euler-type scheme incorporating collision-handling at the…

Numerical Analysis · Mathematics 2025-12-10 B. Leimkuhler , A. Sharma , M. V. Tretyakov

Physical systems can often be described via a continuous-time dynamical system. In practice, the true system is often unknown and has to be learned from measurement data. Since data is typically collected in discrete time, e.g. by sensors,…

Machine Learning · Computer Science 2024-01-31 Katharina Ensinger , Nicholas Tagliapietra , Sebastian Ziesche , Sebastian Trimpe

A method for time-reversible numerical integration of the deterministic Landau-Lifshitz Gilbert equation by means of a second order Suzuki-Trotter decomposition is presented and tested against commonly used second order predictor-corrector…

In previous papers, explicit symplectic integrators were designed for nonrotating black holes, such as a Schwarzschild black hole. However, they fail to work in the Kerr spacetime because not all variables can be separable, or not all…

General Relativity and Quantum Cosmology · Physics 2021-06-24 Xin Wu , Ying Wang , Wei Sun , Fuyao Liu

A numerical integration method for guiding-center orbits of charged particles in toroidal fusion devices with three-dimensional field geometry is described. Here, high order interpolation of electromagnetic fields in space is replaced by a…

Plasma Physics · Physics 2020-12-11 M. Eder , C. G. Albert , L. M. P. Bauer , S. V. Kasilov , W. Kernbichler

In this paper, we consider the task of efficiently computing the numerical solution of evolutionary complex Ginzburg--Landau equations on Cartesian product domains with homogeneous Dirichlet/Neumann or periodic boundary conditions. To this…

Numerical Analysis · Mathematics 2024-06-19 Marco Caliari , Fabio Cassini

Gaussian Mixture Models (GMMs) are one of the most potent parametric density models used extensively in many applications. Flexibly-tied factorization of the covariance matrices in GMMs is a powerful approach for coping with the challenges…

Machine Learning · Computer Science 2023-11-14 Mohammad Pasande , Reshad Hosseini , Babak Nadjar Araabi

Variational integrators for Lagrangian dynamical systems provide a systematic way to derive geometric numerical methods. These methods preserve a discrete multisymplectic form as well as momenta associated to symmetries of the Lagrangian…

Numerical Analysis · Mathematics 2017-10-05 Michael Kraus , Omar Maj

It is well known that symplectic integrators lose their near energy preservation properties when variable step sizes are used. The most common approach to combine adaptive step sizes and symplectic integrators involves the Poincar\'e…

Numerical Analysis · Mathematics 2021-06-25 Valentin Duruisseaux , Jeremy Schmitt , Melvin Leok

Symplectic schemes are powerful methods for numerically integrating Hamiltonian systems, and their long-term accuracy and fidelity have been proved both theoretically and numerically. However direct applications of standard symplectic…

Plasma Physics · Physics 2019-06-26 Jianyuan Xiao , Hong Qin

Geometric numerical integration has recently been exploited to design symplectic accelerated optimization algorithms by simulating the Lagrangian and Hamiltonian systems from the variational framework introduced in Wibisono et al. In this…

Optimization and Control · Mathematics 2023-05-19 Valentin Duruisseaux , Melvin Leok

We develop and analyze several different second-order algorithms for computing a near-optimal solution path of a convex parametric optimization problem with smooth Hessian. Our algorithms are inspired by a differential equation perspective…

Optimization and Control · Mathematics 2023-06-16 Heyuan Liu , Paul Grigas

In this paper, an implicit nonsymplectic exact energy-preserving integrator is specifically designed for a ten-dimensional phase-space conservative Hamiltonian system with five degrees of freedom. It is based on a suitable…

General Relativity and Quantum Cosmology · Physics 2021-04-16 Shiyang Hu , Xin Wu , Enwei Liang

We give a priori error estimates of second order in time fully explicit Runge-Kutta discontinuous Galerkin schemes using upwind fluxes to smooth solutions of scalar fractional conservation laws in one space dimension. Under the time step…

Numerical Analysis · Mathematics 2024-02-27 Fabio Leotta , Jan Giesselmann

This work extends the high-resolution isogeometric analysis approach established for scalar transport equations to the equations of gas dynamics. The group finite element formulation is adopted to obtain an efficient assembly procedure for…

Numerical Analysis · Mathematics 2018-10-01 Matthias Möller , Andrzej Jaeschke

This paper proposes a higher-order multiscale computational method for nonlinear thermo-electric coupling problems of composite structures, which possess temperature-dependent material properties and nonlinear Joule heating. The innovative…

Numerical Analysis · Mathematics 2025-01-24 Hao Dong , Zongze Yang , Yufeng Nie

In this paper, we propose a first-order Fourier integrator for solving the cubic nonlinear Schr\"odinger equation in one dimension. The scheme is explicit and can be implemented using the fast Fourier transform. By a rigorous analysis, we…

Numerical Analysis · Mathematics 2020-10-07 Yifei Wu , Fangyan Yao

Multiderivative time integrators have a long history of development for ordinary differential equations, and yet to date, only a small subset of these methods have been explored as a tool for solving partial differential equations (PDEs).…

Numerical Analysis · Mathematics 2013-10-01 David C. Seal , Yaman Güçlü , Andrew J. Christlieb