English
Related papers

Related papers: Action-Driven Flows for Causal Variational Princip…

200 papers

We derive causal relativistic fluid dynamical equations from the relaxation model of kinetic theory as in a procedure previously applied in the case of non-relativistic rarefied gases. By treating space and time on an equal footing and…

General Relativity and Quantum Cosmology · Physics 2011-08-03 Xinzhong Chen , Edward A Spiegel

Euler-Lagrange variational principle is used to obtain analytical and numerical flow relations in cylindrical tubes. The method is based on minimizing the total stress in the flow duct using the fluid constitutive relation between stress…

Fluid Dynamics · Physics 2013-11-12 Taha Sochi

We prove that autoparallel curves associated with a torsion-free but not necessarily metric-compatible affine connection can be derived from an action principle. We explicitly construct the action functional and show by standard variational…

Mathematical Physics · Physics 2026-03-13 Lavinia Heisenberg

This monograph introduces the basic concepts of the theory of causal fermion systems, a recent approach to the description of fundamental physics. The theory yields quantum mechanics, general relativity and quantum field theory as limiting…

Mathematical Physics · Physics 2018-10-12 Felix Finster

We further develop a recently introduced variational principle of stationary action for problems in nonconservative classical mechanics and extend it to classical field theories. The variational calculus used is consistent with an initial…

Mathematical Physics · Physics 2014-12-10 Chad R. Galley , David Tsang , Leo C. Stein

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

This paper studies the continuous-time dynamics generated by control-theoretic Lagrangian methods for equality-constrained optimization. In particular, we consider dynamics induced by proportional-integral and feedback linearization…

Optimization and Control · Mathematics 2026-05-26 Simone Pirrera , Francesco Ripa , Daniele Astolfi , Vito Cerone , Sophie M. Fosson , Diego Regruto

This study presents a conditional flow matching framework for solving physics-constrained Bayesian inverse problems. In this setting, samples from the joint distribution of inferred variables and measurements are assumed available, while…

Invariant conditions for conformable fractional problems of the calculus of variations under the presence of external forces in the dynamics are studied. Depending on the type of transformations considered, different necessary conditions of…

Optimization and Control · Mathematics 2017-04-14 Matheus J. Lazo , Delfim F. M. Torres

Selfdual variational principles are introduced in order to construct solutions for Hamiltonian and other dynamical systems which satisfy a variety of linear and nonlinear boundary conditions including many of the standard ones. These…

Analysis of PDEs · Mathematics 2007-05-23 Nassif Ghoussoub , Abbas Moameni

Learning-based models for fluid dynamics often operate in unconstrained function spaces, leading to physically inadmissible, unstable simulations. While penalty-based methods offer soft regularization, they provide no structural guarantees,…

Machine Learning · Computer Science 2026-03-26 Xigui Li , Hongwei Zhang , Ruoxi Jiang , Deshu Chen , Chensen Lin , Limei Han , Yuan Qi , Xin Guo , Yuan Cheng

A general set of fluid equations that allow for energy-conserving momentum transport by gyroscopic motion of fluid elements is obtained. The equations are produced by a class of action principles that yield a large subset of the known fluid…

Plasma Physics · Physics 2015-06-22 M. Lingam , P. J. Morrison

In measurement-based quantum computing (MBQC), computation is carried out by a sequence of measurements and corrections on an entangled state. Flow, and related concepts, are powerful techniques for characterising the dependence of the…

Quantum Physics · Physics 2023-10-25 Robert I. Booth , Damian Markham

We introduce a class of variational principles on measure spaces which are causal in the sense that they generate a relation on pairs of points, giving rise to a distinction between spacelike and timelike separation. General existence…

Mathematical Physics · Physics 2014-04-23 Felix Finster

This paper studies stochastic control problems with the action space taken to be probability measures, with the objective penalised by the relative entropy. We identify suitable metric space on which we construct a gradient flow for the…

Optimization and Control · Mathematics 2024-01-26 David Šiška , Łukasz Szpruch

Foundations of a new projection-based model reduction approach for convection dominated nonlinear fluid flows are summarized. In this method the evolution of the flow is approximated in the Lagrangian frame of reference. Global basis…

Fluid Dynamics · Physics 2021-10-05 Rambod Mojgani , Maciej Balajewicz

We investigate a family of approximate multi-step proximal point methods, framed as implicit linear discretizations of gradient flow. The resulting methods are multi-step proximal point methods, with similar computational cost in each…

Optimization and Control · Mathematics 2025-01-15 Yushen Huang , Yifan Sun

In this paper we consider a ``flow'' of nonparametric solutions of the volume constrained Plateau problem with respect to a convex planar curve. Existence and regularity is obtained from standard elliptic theory, and convexity results for…

Differential Geometry · Mathematics 2016-09-07 John McCuan

We present the method for computation of fluid flows that are characterized by the large degree of expansion/contraction and in which the fluid velocity is dominated by the bulk component associated with the expansion/contraction and/or…

Astrophysics · Physics 2015-06-24 A. Y. Poludnenko , A. M. Khokhlov

In this study, we address causal inference when only observational data and a valid causal ordering from the causal graph are available. We introduce a set of flow models that can recover component-wise, invertible transformation of…

Machine Learning · Computer Science 2024-12-16 Minh Khoa Le , Kien Do , Truyen Tran