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We discuss a new geometric construction of port-Hamiltonian systems. Using this framework, we revisit the notion of interconnection providing it with an intrinsic description. Special emphasis on theoretical and applied examples is given…

Mathematical Physics · Physics 2018-08-29 M. Barbero-Liñán , H. Cendra , E. García-Toraño Andrés , D. Martín de Diego

We define partial differential (PD in the following), i.e., field theoretic analogues of Hamiltonian systems on abstract symplectic manifolds and study their main properties, namely, PD Hamilton equations, PD Noether theorem, PD Poisson…

Differential Geometry · Mathematics 2013-10-08 L. Vitagliano

This paper presents a mathematical framework for analyzing machine learning models through the geometry of their induced partitions. By representing partitions as Riemannian simplicial complexes, we capture not only adjacency relationships…

Machine Learning · Computer Science 2025-08-05 Pawel Gajer , Jacques Ravel

Structure-preserving algorithms and algorithms with uniform error bound have constituted two interesting classes of numerical methods. In this paper, we blend these two kinds of methods for solving nonlinear Hamiltonian systems with highly…

Numerical Analysis · Mathematics 2021-02-08 Bin Wang , Yaolin Jiang

Implicative algebras have been recently introduced by Miquel in order to provide a unifying notion of model, encompassing the most relevant and used ones, such as realizability (both classical and intuitionistic), and forcing. In this work,…

Category Theory · Mathematics 2023-12-06 Samuele Maschio , Davide Trotta

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

In this review paper, we consider three kinds of systems of differential equations, which are relevant in physics, control theory and other applications in engineering and applied mathematics; namely: Hamilton equations, singular…

Mathematical Physics · Physics 2016-04-11 Xavier Gràcia , Miguel C. Muñoz-Lecanda , Narciso Román-Roy

We discuss computability and computational complexity of conformal mappings and their boundary extensions. As applications, we review the state of the art regarding computability and complexity of Julia sets, their invariant measures and…

Complex Variables · Mathematics 2017-03-21 Cristobal Rojas , Michael Yampolsky

A symplectic theory approach is devised for solving the problem of algebraic-analytical construction of integral submanifold imbeddings for integrable (via the nonabelian Liouville-Arnold theorem) Hamiltonian systems on canonically…

Dynamical Systems · Mathematics 2015-06-26 Anatoliy K. Prykarpatsky

A geometric derivation of nonholonomic integrators is developed. It is based in the classical technique of generating functions adapted to the special features of nonholonomic systems. The theoretical methodology and the integrators…

Mathematical Physics · Physics 2016-09-07 M. de Leon , D. Martin de Diego , A. Santamaria Merino

We construct a family of canonical connections and surrounding basic theory for almost complex manifolds that are equipped with an affine connection. This framework provides a uniform approach to treating a range of geometries. In…

Differential Geometry · Mathematics 2012-08-06 A. Rod Gover , Pawel Nurowski

Many applications in computational physics that use numerical integrators based on splitting and composition can benefit from the development of optimized algorithms and from choosing the best ordering of terms. The cost in programming and…

Computational Physics · Physics 2022-03-14 Robert I McLachlan

We prove the existence of infinitely many solutions to an elliptic problem by borrowing the techniques from algebraic topology. The solution(s) thus obtained will also be proved to be bounded.

Analysis of PDEs · Mathematics 2021-02-25 A. Panda , D. Choudhuri , A. Bahrouni

For many-particle systems defined on lattices we investigate the global structure of effective Hamiltonians and observables obtained by means of a suitable basis transformation. We study transformations which lead to effective Hamiltonians…

Strongly Correlated Electrons · Physics 2009-11-10 Christian Knetter , Kai P. Schmidt , Goetz S. Uhrig

We suggest a numerical integration procedure for solving the equations of motion of certain classical spin systems which preserves the underlying symplectic structure of the phase space. Such symplectic integrators have been successfully…

Statistical Mechanics · Physics 2007-05-23 Robin Steinigeweg , Heinz-Jürgen Schmidt

Implicit computational complexity, which aims at characterizing complexity classes by machine-independent means, has traditionally been based, on the one hand, on programs and deductive formalisms for free algebras, and on the other hand on…

Logic in Computer Science · Computer Science 2018-02-12 Daniel Leivant , Jean-Yves Marion

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

In this paper, we develop high-order splitting methods for linear port-Hamiltonian systems, focusing on preserving their intrinsic structure, particularly the dissipation inequality. Port-Hamiltonian systems are characterized by their…

Mathematical Physics · Physics 2024-09-16 Marius Mönch , Nicole Marheineke

Several integrability problems of differential equations are addressed by using the concept of $\mathcal{C}^{\infty}$-structure, a recent generalization of the notion of solvable structure. Specifically, the integration procedure associated…

Exactly Solvable and Integrable Systems · Physics 2023-10-25 A. J. Pan-Collantes , C. Muriel , A. Ruiz

In this chapter, we identify fundamental geometric structures that underlie the problems of sampling, optimisation, inference and adaptive decision-making. Based on this identification, we derive algorithms that exploit these geometric…