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Related papers: Newton's discrete dynamics

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In this note we approach the classical, Newtonian, gravitational $N$-body problem by mean of a new, original numerical integration method. After a short summary of the fundamental characteristics of the problem, including a sketch of some…

Computational Physics · Physics 2020-01-08 V. Parisi , R. Capuzzo-Dolcetta

Action at distance in Newtonian physics is replaced by finite propagation speeds in classical post--Newtonian physics. As a result, the differential equations of motion in Newtonian physics are replaced by functional differential equations,…

General Physics · Physics 2011-08-31 Jaume Giné

Newton revealed an underlying duality relation between power potentials in classical mechanics. In this paper, we establish the quantum version of the Newton duality. The main aim of this paper is threefold: (1) first generalizing the…

Mathematical Physics · Physics 2018-03-20 Wen-Du Li , Wu-Sheng Dai

Differential equations based on physical principals are used to represent complex dynamic systems in all fields of science and engineering. Through repeated use in both academics and industry, these equations have been shown to represent…

Methodology · Statistics 2022-09-08 Joshua S. North , Christopher K. Wikle , Erin M. Schliep

Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rates are typically very slow. This paper introduces a family of…

Optimization and Control · Mathematics 2011-04-07 M. Zargham , A. Ribeiro , A. Jadbabaie , A. Ozdaglar

We propose a distributed cubic regularization of the Newton method for solving (constrained) empirical risk minimization problems over a network of agents, modeled as undirected graph. The algorithm employs an inexact, preconditioned Newton…

Optimization and Control · Mathematics 2021-06-21 Amir Daneshmand , Gesualdo Scutari , Pavel Dvurechensky , Alexander Gasnikov

The paper starts with a concise description of the recently developed semismooth* Newton method for the solution of general inclusions. This method is then applied to a class of variational inequalities of the second kind. As a result, one…

Optimization and Control · Mathematics 2020-07-23 Helmut Gfrerer , Jiri V. Outrata , Jan Valdman

Incorporating the Hamiltonian structure of physical dynamics into deep learning models provides a powerful way to improve the interpretability and prediction accuracy. While previous works are mostly limited to the Euclidean spaces, their…

Machine Learning · Computer Science 2022-10-04 Oswin So , Gongjie Li , Evangelos A. Theodorou , Molei Tao

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

We describe the main ingredients needed to create, from the smooth lagrangian density, a variational principle for discrete motions of a discrete rod, with corresponding conserved Noether currents. We describe all geometrical objects in…

Mathematical Physics · Physics 2023-10-19 Ana C. Casimiro , Cesar Rodrigo

The viscous interaction of fluid is understood as the response to deformation, which is proportional to the strain rate. This model has gradually become the standard since Stokes, and has become the basis of the classical flow theory,…

Fluid Dynamics · Physics 2023-06-27 Jian He , Jin Wang , Qiaocong Kong , Penglong Zhao , Xiaoshu Cai , Xiaohang Zhang , Wennan Zou

Riemann's principle "force equals geometry" provided the basis for Einstein's General Relativity - the geometric theory of gravitation. In this paper, we follow this principle to derive the dynamics for any static, conservative force. The…

General Physics · Physics 2019-12-19 Y. Friedman , T. Scarr , J. Steiner

Optimization is at the heart of machine learning, statistics and many applied scientific disciplines. It also has a long history in physics, ranging from the minimal action principle to finding ground states of disordered systems such as…

Optimization and Control · Mathematics 2021-05-11 Guilherme França , Daniel P. Robinson , René Vidal

Numerical solutions to Newton's equations of motion for chaotic self gravitating systems of more than 2 bodies are often regarded to be irreversible. This is due to the exponential growth of errors introduced by the integration scheme and…

Instrumentation and Methods for Astrophysics · Physics 2018-03-14 Simon Portegies Zwart , Tjarda Boekholt

We conduct computer-assisted analysis of the two-dimensional model of a neuron introduced by Chialvo in 1995 (Chaos, Solitons & Fractals 5, 461-479). We apply the method for rigorous analysis of global dynamics based on a set-oriented…

Dynamical Systems · Mathematics 2023-04-05 Paweł Pilarczyk , Justyna Signerska-Rynkowska , Grzegorz Graff

A problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is…

Neural and Evolutionary Computing · Computer Science 2023-11-03 Krzysztof Laddach , Rafał Łangowski

A methodology for deriving dual variational principles for the classical Newtonian mechanics of mass points in the presence of applied forces, interaction forces, and constraints, all with a general dependence on particle velocities and…

Mathematical Physics · Physics 2024-07-02 Amit Acharya , Ambar N. Sengupta

We present a natural proof of Kepler's law of ellipses in the spirit of Euclidean geometry. Moreover we discuss two existing Euclidean geometric proofs, one by Feynman in hist Lost Lecture from 1964 and the other by Newton in the Principia…

Symplectic Geometry · Mathematics 2007-08-01 Maris van Haandel , Gert Heckman

Algorithms of numeric (in exact arithmetic) deduction of analytical expressions, proposed and described by Shevchenko and Vasiliev (1993), are developed and implemented in a computer algebra code. This code is built as a superstructure for…

Symbolic Computation · Computer Science 2016-07-08 Ivan I. Shevchenko

A discrete system constituted of particles interacting by means of a centroid-based law is numerically investigated. The elements of the system move in the plane, and the range of the interaction can be varied from a more local form…

Soft Condensed Matter · Physics 2020-04-22 A. Battista , L. Rosa , L. Greco , R. dell'Erba