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Riemannian geometry provides the fundamental framework for optimization on nonlinear spaces such as matrix manifolds, which arise in machine learning, signal processing, and robotics. While the underlying theory is classical, existing…

Differential Geometry · Mathematics 2026-05-05 Benyamin Ghojogh

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

In this paper, we develop a structure-preserving discretization of the Lagrangian framework for electromagnetism, combining techniques from variational integrators and discrete differential forms. This leads to a general family of…

Numerical Analysis · Mathematics 2015-11-05 Ari Stern , Yiying Tong , Mathieu Desbrun , Jerrold E. Marsden

Geometric integration of non-autonomous classical engineering problems, such as rotor dynamics, is investigated. It is shown, both numerically and by backward error analysis, that geometric (structure preserving) integration algorithms are…

Numerical Analysis · Mathematics 2011-03-11 Klas Modin

We address the problem of constructing numerical integrators for nonholonomic Lagrangian systems that enjoy appropriate discrete versions of the geometric properties of the continuous flow, including the preservation of energy. Building on…

Numerical Analysis · Mathematics 2025-10-20 Jorge Cortes

In this paper we make an overview of results relating the recent "discoveries" in differential geometry, such as higher structures and differential graded manifolds with some natural problems coming from mechanics. We explain that a lot of…

Mathematical Physics · Physics 2021-03-17 Vladimir Salnikov , Aziz Hamdouni , Daria Loziienko

In this Thesis we develop the geometric formulations for higher-order autonomous and non-autonomous dynamical systems, and second-order field theories. In all cases, the physical information of the system is given in terms of a Lagrangian…

Mathematical Physics · Physics 2014-10-30 Pedro D. Prieto-Martínez

The aim of the present text is twofold: to provide a compendium of Lagrangian and Hamiltonian geometries and to introduce and investigate new analytical Mechanics: Finslerian, Lagrangian and Hamiltonian. The fundamental equations (or…

Differential Geometry · Mathematics 2012-03-20 Radu Miron

We develop a geometric version of the inverse problem of the calculus of variations for discrete mechanics and constrained discrete mechanics. The geometric approach consists of using suitable Lagrangian and isotropic submanifolds. We also…

Differential Geometry · Mathematics 2018-05-09 María Barbero-Liñán , Marta Farré Puiggalí , Sebastián Ferraro , David Martín de Diego

A variational framework for accelerated optimization was recently introduced on normed vector spaces and Riemannian manifolds in Wibisono et al. (2016) and Duruisseaux and Leok (2021). It was observed that a careful combination of…

Optimization and Control · Mathematics 2023-05-16 Valentin Duruisseaux , Melvin Leok

A variational formulation of accelerated optimization on normed spaces was recently introduced by considering a specific family of time-dependent Bregman Lagrangian and Hamiltonian systems whose corresponding trajectories converge to the…

Optimization and Control · Mathematics 2022-01-11 Valentin Duruisseaux , Melvin Leok

In this paper, we describe a geometric setting for higher-order lagrangian problems on Lie groups. Using left-trivialization of the higher-order tangent bundle of a Lie group and an adaptation of the classical Skinner-Rusk formalism, we…

Mathematical Physics · Physics 2011-04-19 Leonardo Colombo , David Martin de Diego

We re-examine classical mechanics with both commuting and anticommuting degrees of freedom. We do this by defining the phase dynamics of a general Lagrangian system as an implicit differential equation in the spirit of Tulczyjew. Rather…

Mathematical Physics · Physics 2018-04-26 Andrew James Bruce , Katarzyna Grabowska , Giovanni Moreno

Hamiltonian systems of ordinary and partial differential equations are fundamental mathematical models spanning virtually all physical scales. A critical property for the robustness and stability of computational methods in such systems is…

Quantum Physics · Physics 2025-02-25 Hsuan-Cheng Wu , Xiantao Li

Recently, continuous-time dynamical systems have proved useful in providing conceptual and quantitative insights into gradient-based optimization, widely used in modern machine learning and statistics. An important question that arises in…

Optimization and Control · Mathematics 2021-04-29 Guilherme França , Michael I. Jordan , René Vidal

Most physical processes posses structural properties such as constant energies, volumes, and other invariants over time. When learning models of such dynamical systems, it is critical to respect these invariants to ensure accurate…

Machine Learning · Computer Science 2022-01-11 Katharina Ensinger , Friedrich Solowjow , Sebastian Ziesche , Michael Tiemann , Sebastian Trimpe

Lagrangian multiforms provide a variational framework for describing integrable hierarchies. This thesis presents two approaches for systematically constructing Lagrangian one-forms, which cover the case of finite-dimensional integrable…

Mathematical Physics · Physics 2026-02-13 Anup Anand Singh

This paper proposes an original Riemmanian geometry for low-rank structured elliptical models, i.e., when samples are elliptically distributed with a covariance matrix that has a low-rank plus identity structure. The considered geometry is…

Differential Geometry · Mathematics 2020-01-07 Florent Bouchard , Arnaud Breloy , Guillaume Ginolhac , Alexandre Renaux , Frédéric Pascal

This paper formulates optimal control problems for rigid bodies in a geometric manner and it presents computational procedures based on this geometric formulation for numerically solving these optimal control problems. The dynamics of each…

Optimization and Control · Mathematics 2008-05-07 Taeyoung Lee , Melvin Leok , N. Harris McClamroch

The classical notion of retraction map used to approximate geodesics is extended and rigorously defined to become a powerful tool to construct geometric integrators and it is called discretization map. Using the geometry of the tangent and…

Numerical Analysis · Mathematics 2022-06-20 María Barbero Liñán , David Martín de Diego