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We use a reinforcement learning approach to reduce entropy production in a closed quantum system brought out of equilibrium. Our strategy makes use of an external control Hamiltonian and a policy gradient technique. Our approach bears no…

Quantum Physics · Physics 2024-02-21 Sofia Sgroi , G. Massimo Palma , Mauro Paternostro

By extracting unstable invariant solutions directly from body-forced three-dimensional turbulence, we study the dynamical processes at play when the forcing is large scale and either unidirectional in the momentum or the vorticity…

Fluid Dynamics · Physics 2017-04-26 Dan Lucas , Rich Kerswell

Simulating transition dynamics between metastable states is a fundamental challenge in dynamical systems and stochastic processes with wide real-world applications in understanding protein folding, chemical reactions and neural activities.…

Machine Learning · Computer Science 2024-10-22 Haibo Wang , Yuxuan Qiu , Yanze Wang , Rob Brekelmans , Yuanqi Du

We develop a flux-conservative formalism for a Newtonian multi-fluid system, including dissipation and entrainment (i.e. allowing the momentum of one fluid to be a linear combination of the velocities of all fluids). Maximum use is made of…

Fluid Dynamics · Physics 2016-09-08 Nils Andersson , G. L. Comer

Biological machines like molecular motors and enzymes operate in dynamic cycles representable as stochastic flows on networks. Current stochastic dynamics describes such flows on fixed networks. Here, we develop a scalable approach to…

Statistical Mechanics · Physics 2026-03-02 Ying-Jen Yang , Ken A. Dill

By solving a simple kinetic equation, in the relaxation time approximation, and for a particular set of moments of the distribution function, we establish a set of equations which, on the one hand, capture exactly the dynamics of the…

Nuclear Theory · Physics 2018-03-07 Jean-Paul Blaizot , Li Yan

The design of flow control systems remains a challenge due to the nonlinear nature of the equations that govern fluid flow. However, recent advances in computational fluid dynamics (CFD) have enabled the simulation of complex fluid flows…

Computational Engineering, Finance, and Science · Computer Science 2018-11-13 Jeremy Morton , Freddie D. Witherden , Antony Jameson , Mykel J. Kochenderfer

We describe a method to extract from experimental data the important dynamical modes in spatio-temporal patterns in a system driven out of thermodynamic equilibrium. Using a novel optical technique for controlling fluid flow, we create an…

Fluid Dynamics · Physics 2011-05-03 Adam C. Perkins , Roman O. Grigoriev , Michael F. Schatz

We study the dynamics of inertial particles in turbulence using datasets obtained from both direct numerical simulations and laboratory experiments of turbulent swirling flows. By analyzing time series of particle velocity increments at…

We propose a physics-constrained machine learning method-based on reservoir computing- to time-accurately predict extreme events and long-term velocity statistics in a model of turbulent shear flow. The method leverages the strengths of two…

Fluid Dynamics · Physics 2021-04-14 Nguyen Anh Khoa Doan , Wolfgang Polifke , Luca Magri

We consider a continuum model for the dynamics of systems of self propelling particles with kinematic constraints on the velocities. The model aims to be analogous to a discrete algorithm used in works by T. Vicsek et al. In this paper we…

Fluid Dynamics · Physics 2009-12-16 V. I. Ratushnaya , V. L. Kulinskii , A. V. Zvelindovsky , D. Bedeaux

A scheme to control the many-boson tunneling process to open space is derived and demonstrated. The number of ejected particles and their velocities can be controlled by two parameters, the threshold of the potential and the interparticle…

Many applications of computational fluid dynamics require multiple simulations of a flow under different input conditions. In this paper, a numerical algorithm is developed to efficiently determine a set of such simulations in which the…

Numerical Analysis · Mathematics 2017-05-29 Max Gunzburger , Nan Jiang , Zhu Wang

We present a novel method for guaranteeing linear momentum in learned physics simulations. Unlike existing methods, we enforce conservation of momentum with a hard constraint, which we realize via antisymmetrical continuous convolutional…

Machine Learning · Computer Science 2022-11-03 Lukas Prantl , Benjamin Ummenhofer , Vladlen Koltun , Nils Thuerey

Equilibrium thermodynamics is grounded in the law of energy conservation, with a specific focus on how systems exchange energy with their environment during transitions between equilibrium states. These transitions are typically…

Statistical Mechanics · Physics 2024-08-19 Karol Makuch

Atmospheric flows exhibit long-range spatiotemporal correlations manifested as the fractal geometry to the global cloud cover pattern concomitant with inverse power-law form for power spectra of temporal fluctuations of all scales ranging…

General Physics · Physics 2007-05-23 A. M. Selvam , S. Fadnavis

For configurational changes of soft matter systems affected or caused by external hydrodynamic flow, we identify applied work, exchanged heat, and entropy change on the level of a single trajectory. These expressions guarantee invariance of…

Soft Condensed Matter · Physics 2009-01-15 Thomas Speck , Jakob Mehl , Udo Seifert

In the Newtonian limit of $f(R)$ gravity, for an isolated self-gravitating system consisting of $N$ extended fluid bodies, the inter-body dynamics are studied by applying the symmetric and trace-free formalism in terms of irreducible…

General Relativity and Quantum Cosmology · Physics 2025-12-30 Bofeng Wu , Xiao Zhang

This study proposes the topology optimization method for moving rigid bodies subjected to forces from fluid flow, such as sails and turbines, with an unsteady time-dependent formulation. Unlike existing topology optimization frameworks in…

Fluid Dynamics · Physics 2026-01-27 Yuta Tanabe , Kentaro Yaji , Kuniharu Ushijima

We present a series of three-dimensional discrete Boltzmann (DB) models for compressible flows in and out of equilibrium. The key formulating technique is the construction of discrete equilibrium distribution function through inversely…

Fluid Dynamics · Physics 2018-03-06 Yanbiao Gan , Aiguo Xu , Guangcai Zhang , Huilin Lai