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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

Flow matching trains a neural velocity field by regression against a target velocity associated with a prescribed probability path connecting a simple initial distribution to the data distribution. A central design choice is the path…

Machine Learning · Computer Science 2026-05-21 Shukai Du , Junzhe Zhang , Yiming Li

We study the problem of building an efficient learning system. Efficient learning processes information in the least time, i.e., building a system that reaches a desired error threshold with the least number of observations. Building upon…

Machine Learning · Computer Science 2025-09-26 Siyuan Guo , Bernhard Schölkopf

The wave nature of heat flow mechanisms, such as lattice waves is discussed. Tan and Holland's Tangent Law of heat flow refraction is reviewed. A classroom demonstration of heat flow refraction through conductors in series is presented, and…

Physics Education · Physics 2014-05-22 Mark Ciotola , Olivia Mah

In physics, there is a scalar function called the action which behaves like a cost function. When minimized, it yields the "path of least action" which represents the path a physical system will take through space and time. This function is…

Machine Learning · Computer Science 2023-03-06 Tim Strang , Isabella Caruso , Sam Greydanus

The refraction of a light ray by a homogeneous, isotropic and non-dispersive transparent material half-space in uniform rectilinear motion is investigated theoretically. The approach is an amalgamation of the original Fermat's principle and…

Optics · Physics 2007-12-06 Aleksandar Gjurchinovski , Aleksandar Skeparovski

This paper proposes a theory for understanding perceptual learning processes within the general framework of laws of nature. Neural networks are regarded as systems whose connections are Lagrangian variables, namely functions depending on…

Computer Vision and Pattern Recognition · Computer Science 2018-08-29 Alessandro Betti , Marco Gori , Stefano Melacci

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

A dual formalism for Lagrange multipliers is developed. The formalism is used to minimize an action function $S(q_2,q_1,T)$ without any dynamical input other than that $S$ is convex. All the key equations of analytical mechanics -- the…

Classical Physics · Physics 2021-09-21 David J. Tannor

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

We consider the problem of a particle traveling from an initial configuration to a final configuration (given by a point in the plane along with a prescribed velocity vector) in minimum time with non-homogeneous velocity and with…

Optimization and Control · Mathematics 2014-01-13 Ricardo G. Sanfelice , Sze Zheng Yong , Emilio Frazzoli

In this paper, we show that the difficulties of interpretation of the principle of least action concerning "final causes" or "efficient causes" are due to the existence of two different actions, the "Euler-Lagrange action" (or classical…

Quantum Physics · Physics 2015-05-13 Michel Gondran , Alexandre Gondran

We investigate the optimal transport problem between probability measures when the underlying cost function is understood to satisfy a least action principle, also known as a Lagrangian cost. These generalizations are useful when connecting…

Machine Learning · Computer Science 2024-06-04 Aram-Alexandre Pooladian , Carles Domingo-Enrich , Ricky T. Q. Chen , Brandon Amos

Smartphones may be seen as miniature toolboxs to perform Physics experiments. In this paper, we present three different "optics workbenches" mainly based on the light meter of a smartphone. One is aimed at the precise study of Malus law and…

This chapter derives the properties of light from the properties of processing, including its ability to be both a wave and a particle, to respond to objects it doesn't physically touch, to take all paths to a destination, to choose a route…

Other Computer Science · Computer Science 2012-07-16 B. Whitworth

In this work, we present a detailed procedure of computer implementation of the laws of refraction and reflection on an arbitrary surface with rotational symmetry with respect to the propagation axis. The goal is to facilitate the…

Optics · Physics 2025-01-07 J. E. Gómez-Correa , A. L. Padilla-Ortiz , S. Chávez-Cerda

Finding optimal trajectories for multiple traffic demands in a congested network is a challenging task. Optimal transport theory is a principled approach that has been used successfully to study various transportation problems. Its usage is…

Physics and Society · Physics 2024-10-10 Abdullahi Adinoyi Ibrahim , Michael Muehlebach , Caterina De Bacco

We introduce a new method for generating initial conditions consistent with highly nonlinear observations of density and velocity fields. Using a variant of the Least Action method, called Perturbative Least Action (PLA), we show that it is…

Astrophysics · Physics 2011-02-11 David M. Goldberg , David N. Spergel

Light reflection plays a crucial role in a number of modern technologies. In this paper, analytical expressions for maximal reflected power in any direction and for any polarization are given for generic planar structures made of a single…

Optics · Physics 2022-08-12 Mohamed Ismail Abdelrahman , Francesco Monticone

We determine the globally minimum time $T$ needed to translate a thin submerged flat plate a given distance parallel to its surface within a work budget. The Reynolds number for the flow is assumed to be large so that the drag on the plate…

Fluid Dynamics · Physics 2021-01-25 S. Mandre
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