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Related papers: Stochastic Lie group integrators

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We propose a method to construct the stochastic integral simultaneously under a non-dominated family of probability measures. Path-by-path, and without referring to a probability measure, we construct a sequence of Lebesgue-Stieltjes…

Probability · Mathematics 2012-06-21 Marcel Nutz

Stochastic evolution underpins several approaches to the dynamics of open quantum systems, such as random modulation of Hamiltonian parameters, the stochastic Schrodinger equation (SSE), and the stochastic Liouville equation (SLE). These…

Quantum Physics · Physics 2026-01-22 Pietro De Checchi , Federico Gallina , Barbara Fresch , Giulio G. Giusteri

We propose a method for developing the flows of stochastic dynamical systems, posed as Ito's stochastic differential equations, on a Riemannian manifold identified through a suitably constructed metric. The framework used for the stochastic…

Mathematical Physics · Physics 2020-07-24 Mariya Mamajiwala , Debasish Roy

A notion of implicit difference equation on a Lie groupoid is introduced and an algorithm for extracting the integrable part (backward or/and forward) is formulated. As an application, we prove that discrete Lagrangian dynamics on a Lie…

Differential Geometry · Mathematics 2011-04-04 D. Iglesias , J. C. Marrero , D. Martin de Diego , E. Padron

In this paper, a physics-oriented stochastic kinetic scheme will be developed that includes random inputs from both flow and electromagnetic fields via a hybridization of stochastic Galerkin and collocation methods. Based on the BGK-type…

Computational Physics · Physics 2021-03-17 Tianbai Xiao , Martin Frank

A numerical approach for the approximation of inertial manifolds of stochastic evolutionary equations with multiplicative noise is presented and illustrated. After splitting the stochastic evolutionary equations into a backward and a…

Dynamical Systems · Mathematics 2012-06-22 Xingye Kan , Jinqiao Duan , Ioannis G. Kevrekidis , Anthony J. Roberts

Locally Linear Embedding (LLE) is a nonlinear spectral dimensionality reduction and manifold learning method. It has two main steps which are linear reconstruction and linear embedding of points in the input space and embedding space,…

Machine Learning · Statistics 2021-04-06 Benyamin Ghojogh , Ali Ghodsi , Fakhri Karray , Mark Crowley

The stochastic-gauge representation is a method of mapping the equation of motion for the quantum mechanical density operator onto a set of equivalent stochastic differential equations. One of the stochastic variables is termed the…

Quantum Physics · Physics 2010-11-02 Mark R. Dowling , Matthew J. Davis , Peter D. Drummond , Joel F. Corney

In this paper, we efficiently compute overapproximating reachable sets for control systems evolving on Lie groups, building off results from monotone systems theory and geometric integration theory. We consider intervals in the tangent…

Systems and Control · Electrical Eng. & Systems 2024-08-22 Akash Harapanahalli , Samuel Coogan

We consider the mathematical analysis and numerical approximation of a system of nonlinear partial differential equations that arises in models that have relevance to steady isochoric flows of colloidal suspensions. The symmetric velocity…

Numerical Analysis · Mathematics 2021-08-09 Andrea Bonito , Vivette Girault , Diane Guignard , Kumbakonam R. Rajagopal , Endre Süli

We introduce a nonlinear stochastic model reduction technique for high-dimensional stochastic dynamical systems that have a low-dimensional invariant effective manifold with slow dynamics, and high-dimensional, large fast modes. Given only…

Machine Learning · Statistics 2023-10-25 Felix X. -F. Ye , Sichen Yang , Mauro Maggioni

We propose a generalization of nonlinear stability of numerical one-step integrators to Riemannian manifolds in the spirit of Butcher's notion of B-stability. Taking inspiration from Simpson-Porco and Bullo, we introduce non-expansive…

Numerical Analysis · Mathematics 2024-02-09 Martin Arnold , Elena Celledoni , Ergys Çokaj , Brynjulf Owren , Denise Tumiotto

We develop a Bayesian methodology for numerical solution of the incompressible Navier--Stokes equations with quantified uncertainty. The central idea is to treat discretized Navier--Stokes dynamics as a state-space model and to view…

Computation · Statistics 2026-02-04 Nicholas Polson , Vadim Sokolov

This paper investigates the two-dimensional stochastic steady-state Navier-Stokes(NS) equations with additive random noise. We introduce an innovative splitting method that decomposes the stochastic NS equations into a deterministic NS…

Numerical Analysis · Mathematics 2025-04-23 Jie Zhu , Yujun Zhu , Ju Ming , Max D. Gunzburger

This paper is a study of the Lie groups of point symmetries admitted by a system describing a non-stationary planar flow of an ideal plastic material. For several types of forces involved in the system, the infinitesimal generators which…

Mathematical Physics · Physics 2015-06-23 Vincent Lamothe

We present a general framework for constructing structure-preserving numerical integrators for nonholonomically constrained mechanical systems evolving on Lie groups using retraction maps. Retraction maps generalize the exponential map and…

Numerical Analysis · Mathematics 2026-04-08 Viyom Vivek , David Martin de Diego , Ravi N. Banavar

Through assembling the navigation parameters as matrix Lie group state, the corresponding inertial navigation system (INS) kinematic model possesses a group-affine property. The Lie logarithm of the navigation state estimation error…

Robotics · Computer Science 2022-08-09 Lubin Chang , Yarong Luo

This paper presents an implicit method for the discrete unified gas-kinetic scheme (DUGKS) to speed up the simulations of the steady flows in all flow regimes. The DUGKS is a multi-scale scheme finite volume method (FVM) for all flow…

Fluid Dynamics · Physics 2018-10-18 Dongxin Pan , Chengwen Zhong , Congshan Zhuo

A stratified Lie system is a nonautonomous system of first-order ordinary differential equations on a manifold $M$ described by a $t$-dependent vector field $X=\sum_{\alpha=1}^rg_\alpha X_\alpha$, where $X_1,\ldots,X_r$ are vector fields on…

Mathematical Physics · Physics 2023-04-25 J. F. Cariñena , J. de Lucas , D. Wysocki

Consider a manifold $M$ endowed locally with a pair of complementary distributions $\Delta^H \oplus \Delta^V=TM$ and let $\text{Diff}(\Delta^H, M)$ and $\text{Diff}(\Delta^V, M)$ be the corresponding Lie subgroups generated by vector fields…

Dynamical Systems · Mathematics 2015-11-05 Alison M. Melo , Leandro Morgado , Paulo R. Ruffino