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For a wide range of phenomena, current computational ability does not always allow for fully atomistic simulations of high-dimensional molecular systems to reach time scales of interest. Coarse-graining (CG) is an established approach to…

Computational Physics · Physics 2020-04-22 Joshua Finkelstein , Giacomo Fiorin , Benjamin Seibold

A simple form of the Boris solver in particle-in-cell (PIC) simulation is proposed. It employs an exact solution of the Lorentz-force part, and it is equivalent to the Boris solver with a gyrophase correction. As a favorable property for…

Computational Physics · Physics 2018-11-20 Seiji Zenitani , Takayuki Umeda

The study of the long time conservation for numerical methods poses interesting and challenging questions from the point of view of geometric integration. In this paper, we analyze the long time energy and magnetic moment conservations of…

Numerical Analysis · Mathematics 2021-10-19 Bin Wang , Xinyuan Wu , Yonglei Fang

This contribution presents an integration method based on the Simpson quadrature. The integrator is designed for finite-dimensional nonlinear mechanical systems that derive from variational principles. The action is discretized using…

Numerical Analysis · Mathematics 2025-12-04 Juan Antonio Rojas-Quintero , François Dubois , Frédéric Jourdan

The goal of this paper is to develop energy-preserving variational integrators for time-dependent mechanical systems with forcing. We first present the Lagrange-d'Alembert principle in the extended Lagrangian mechanics framework and derive…

Numerical Analysis · Mathematics 2018-05-23 Harsh Sharma , Mayuresh Patil , Craig Woolsey

A consequent approach is proposed to construct symplectic force-gradient algorithms of arbitrarily high orders in the time step for precise integration of motion in classical and quantum mechanics simulations. Within this approach the basic…

Statistical Mechanics · Physics 2009-11-07 Igor Omelyan , Ihor Mryglod , Reinhard Folk

A stochastic Forward-Backward algorithm with a constant step is studied. At each time step, this algorithm involves an independent copy of a couple of random maximal monotone operators. Defining a mean operator as a selection integral, the…

Optimization and Control · Mathematics 2018-04-05 Pascal Bianchi , Walid Hachem , Adil Salim

This paper addresses the problem of efficiently computing higher-order variational integrators in simulation and trajectory optimization of mechanical systems as those often found in robotic applications. We develop $O(n)$ algorithms to…

Robotics · Computer Science 2019-04-30 Taosha Fan , Jarvis Schultz , Todd Murphey

A recent reformulation [1] of the problem of Coulomb gases in the presence of a dynamical dielectric medium showed that finite temperature simulations of such systems can be accomplished on the basis of completely local Hamiltonians on a…

Soft Condensed Matter · Physics 2009-11-11 A. Duncan , R. D. Sedgewick

Quantum algorithms have been developed for efficiently solving linear algebra tasks. However, they generally require deep circuits and hence universal fault-tolerant quantum computers. In this work, we propose variational algorithms for…

Quantum Physics · Physics 2021-12-28 Xiaosi Xu , Jinzhao Sun , Suguru Endo , Ying Li , Simon C. Benjamin , Xiao Yuan

An interesting family of geometric integrators for Lagrangian systems can be defined using discretizations of the Hamilton's principle of critical action. This family of geometric integrators is called variational integrators. In this…

Mathematical Physics · Physics 2015-06-16 Leonardo Colombo , David Martín de Diego , Marcela Zuccalli

A variational method is used to derive a self-consistent macro-particle model for relativistic electromagnetic kinetic plasma simulations. Extending earlier work [E. G. Evstatiev and B. A. Shadwick, J. Comput. Phys., vol. 245, pp. 376-398,…

Computational Physics · Physics 2014-04-22 A. B. Stamm , B. A. Shadwick , E. G. Evstatiev

A large hadron machine like the LHC with its high track multiplicities always asks for powerful tools that drastically reduce the large background while selecting signal events efficiently. Actually such tools are widely needed and used in…

Data Analysis, Statistics and Probability · Physics 2014-11-20 Markward Britsch , Nikolai Gagunashvili , Michael Schmelling

We consider the numerical integration of the Gross-Pitaevskii equation with a potential trap given by a time-dependent harmonic potential or a small perturbation thereof. Splitting methods are frequently used with Fourier techniques since…

Numerical Analysis · Mathematics 2011-05-02 Philipp Bader , Sergio Blanes

Numerical simulations of relativistic plasmas have become more feasible, popular, and crucial for various astrophysical sources with the availability of computational resources. The necessity for high-accuracy particle dynamics is…

High Energy Astrophysical Phenomena · Physics 2024-07-24 L. Du Plessis , C. Venter , A. K. Harding , Z. Wadiasingh , C. Kalapotharakos , P. Els

Motivated by far-reaching applications ranging from quantum simulations of complex processes in physics and chemistry to quantum information processing, a broad effort is currently underway to build large-scale programmable quantum systems.…

Capture, selective collection and flight manipulation of airborne particulate are three important functional requirements in various actively growing aerosol technology applications. Aerodynamic drag, particle inertia and dielectrophoretic…

Soft Condensed Matter · Physics 2022-03-16 Pramodt Srinivasula , Rochish M Thaokar

Polynomial approximations to the inverse of the fermion matrix are used to filter the dynamics of the upper energy scales in HMC simulations. The use of a multiple time-scale integration scheme allows the filtered pseudofermions to be…

High Energy Physics - Lattice · Physics 2015-05-28 Waseem Kamleh , Mike Peardon

Robust Markov decision processes (MDPs) allow to compute reliable solutions for dynamic decision problems whose evolution is modeled by rewards and partially-known transition probabilities. Unfortunately, accounting for uncertainty in the…

Machine Learning · Computer Science 2020-06-18 Chin Pang Ho , Marek Petrik , Wolfram Wiesemann

A Hamiltonian formulation of generic many-particle systems with space-dependent balanced loss and gain coefficients is presented. It is shown that the balancing of loss and gain necessarily occurs in a pair-wise fashion. Further, using a…

Mathematical Physics · Physics 2019-08-30 Debdeep Sinha , Pijush K. Ghosh