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A least action principle for damping motion has been previously proposed with a Hamiltonian and a Lagrangian containing the energy dissipated by friction. Due to the space-time nonlocality of the Lagrangian, mathematical uncertainties…

Classical Physics · Physics 2014-12-03 Tongling Lin , Qiuping A. Wang

This work is an analytical calculation of the path probability for random dynamics of mechanical system described by Langevin equation with Gaussian noise. The result shows an exponential dependence of the probability on the action. In the…

Statistical Mechanics · Physics 2015-10-27 Aziz El Kaabouchi , Qiuping A. Wang

The Principle of Least Action has evolved and established itself as the most basic law of physics. This allows us to see how this fundamental law of nature determines the development of the system towards states with less action, i.e.,…

Adaptation and Self-Organizing Systems · Physics 2012-10-08 Atanu Bikash Chatterjee

We review some techniques from non-linear analysis in order to investigate critical paths for the action functional in the calculus of variations applied to physics. Previous attempts to analyse when these are minima ex- ist, but mainly…

Mathematical Physics · Physics 2013-03-22 E. López , A. Molgado , J. A. Vallejo

Despite the importance of the variational principles of physics, there have been relatively few attempts to consider them for a realistic framework. In addition to the old teleological question, this paper continues the recent discussion…

History and Philosophy of Physics · Physics 2019-03-28 Vladislav Terekhovich

Formulating the equations of motion for cosmological bodies (such as galaxies) in an integral, rather than differential, form has several advantages. Using an integral the mathematical instability at early times is avoided and the boundary…

Astrophysics · Physics 2009-10-31 Alan B. Whiting

Machine Learning algorithms are typically regarded as appropriate optimization schemes for minimizing risk functions that are constructed on the training set, which conveys statistical flavor to the corresponding learning problem. When the…

Machine Learning · Computer Science 2019-07-05 Alessandro Betti , Marco Gori

The principle of least action provides a holistic worldview in which nature in its entirety and every detail is pictured in terms of actions. Each and every action is ultimately composed of one or multiples of the most elementary action…

General Physics · Physics 2011-10-27 Arto Annila

We propose a time discretization scheme for a class of ordinary differential equations arising in simulations of fluid/particle flows. The scheme is intended to work robustly in the lubrication regime when the distance between two particles…

Numerical Analysis · Mathematics 2010-03-25 Matthieu Hillairet , Alexei Lozinski , Marcela Szopos

In this note we review the basic mathematical ideas used in finance in the language of modern physics. We focus on discrete time formalism, derive path integral and Green's function formulas for pricing. We also discuss various risk…

Statistical Finance · Quantitative Finance 2020-01-30 A. Jakovac

Small random perturbations may have a dramatic impact on the long time evolution of dynamical systems, and large deviation theory is often the right theoretical framework to understand these effects. At the core of the theory lies the…

Numerical Analysis · Mathematics 2017-10-11 Tobias Grafke , Tobias Schaefer , Eric Vanden-Eijnden

Optimization is finding the best solution, which mathematically amounts to locating the global minimum of some cost function. Optimization is traditionally automated with digital or quantum computers, each having their limitations and none…

Statistical Mechanics · Physics 2021-11-16 Natalia B. Janson , Christopher J. Marsden

In numerical studies of diffusive dynamics, two different action functionals are often used to specify the probability distribution of trajectories, one of which requiring the evaluation of the second derivative of the potential in addition…

Statistical Mechanics · Physics 2008-10-28 Artur B. Adib

In this work, we propose an interesting method that aims to approximate an activation function over some domain by polynomials of the presupposing low degree. The main idea behind this method can be seen as an extension of the ordinary…

Machine Learning · Computer Science 2022-02-02 John Chiang

Nature provides a way to understand physics with reinforcement learning since nature favors the economical way for an object to propagate. In the case of classical mechanics, nature favors the object to move along the path according to the…

Machine Learning · Computer Science 2020-11-30 Zehao Jin , Joshua Yao-Yu Lin , Siao-Fong Li

The least action principle occupies a central part in contemporary physics. Yet, as far as classical field theory is concerned, it may not be as essential as generally thought. We show with three detailed examples of classical interacting…

High Energy Physics - Theory · Physics 2015-02-02 Jacob D. Bekenstein , Bibhas Ranjan Majhi

In spirit of the principle of least action, which means that when a perturbation is applied to a physical system its reaction is such that it modifies its state to "agree" with the perturbation by "minimal" change of its initial state. In…

Plasma Physics · Physics 2015-07-29 Alexander Rokhlenko

Optimization is a major part of human effort. While being mathematical, optimization is also built into physics. For example, physics has the principle of Least Action, the principle of Minimum Entropy Generation, and the Variational…

Emerging Technologies · Computer Science 2020-07-23 Sri Krishna Vadlamani , Tianyao Patrick Xiao , Eli Yablonovitch

The optimal control of a mechanical system is of crucial importance in many realms. Typical examples are the determination of a time-minimal path in vehicle dynamics, a minimal energy trajectory in space mission design, or optimal motion…

Optimization and Control · Mathematics 2008-10-09 S. Ober-Bloebaum , O. Junge , J. E. Marsden

In many situations, one can approximate the behavior of a quantum system, i.e. a wave function subject to a partial differential equation, by effective classical equations which are ordinary differential equations. A general method and…

Mathematical Physics · Physics 2007-05-23 Martin Bojowald , Aureliano Skirzewski
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