English
Related papers

Related papers: Equivariant Hamiltonian Flows

200 papers

Isotropic fluids in two spatial dimensions can break parity symmetry and sustain transverse stresses which do not lead to dissipation. Corresponding transport coefficients include odd viscosity, odd torque, and odd pressure. We consider an…

Fluid Dynamics · Physics 2023-05-10 Gustavo M. Monteiro , Alexander G. Abanov , Sriram Ganeshan

Combination of deep learning and ab initio calculation has shown great promise in revolutionizing future scientific research, but how to design neural network models incorporating a priori knowledge and symmetry requirements is a key…

Computational Physics · Physics 2023-06-12 Xiaoxun Gong , He Li , Nianlong Zou , Runzhang Xu , Wenhui Duan , Yong Xu

Learning permutations is fundamental to sorting, ranking, and matching, but existing differentiable methods based on entropy-regularized Sinkhorn produce a single softened solution and collapse under ambiguity. We present PermFlow, a…

Machine Learning · Computer Science 2026-05-19 Yimeng Min , Carla P. Gomes

This paper surveys results found by the authors in the previous papers (see for example, A. Duyunova, V. Lychagin, S. Tychkov, Differential invariants for spherical layer flows of a viscid fluid, Journal of Geometry and Physics, 130,…

Mathematical Physics · Physics 2020-04-06 Anna Duyunova , Valentin Lychagin , Sergey Tychkov

Dipole-conserving fluids serve as examples of kinematically constrained systems that can be understood on the basis of symmetry. They are known to display various exotic features including glassylike dynamics, subdiffusive transport, and…

Strongly Correlated Electrons · Physics 2023-04-18 Aleksander Głódkowski , Francisco Peña-Benítez , Piotr Surówka

We study certain symplectic quotients of n-fold products of complex projective m-space by the unitary group acting diagonally. After studying nonemptiness and smoothness these quotients we construct the action-angle variables, defined on an…

Symplectic Geometry · Mathematics 2007-05-23 Hermann Flaschka , John Millson

We define a class of machine-learned flow-based sampling algorithms for lattice gauge theories that are gauge-invariant by construction. We demonstrate the application of this framework to U(1) gauge theory in two spacetime dimensions, and…

Flow-based models typically define a latent space with dimensionality identical to the observational space. In many problems, however, the data does not populate the full ambient data space that they natively reside in, rather inhabiting a…

Machine Learning · Statistics 2023-02-24 Mingtian Zhang , Yitong Sun , Chen Zhang , Steven McDonagh

This work is the second part of a program initiated in arXiv:2111.13258 aiming at the development of an intrinsic geometric well-posedness theory for Hamilton-Jacobi equations related to controlled gradient flow problems in metric spaces.…

Analysis of PDEs · Mathematics 2024-01-17 Giovanni Conforti , Richard C. Kraaij , Daniela Tonon

Starting from the vortex filament flow introduced in 1906 by Da Rios, there is a hierarchy of commuting geometric flows on space curves. The traditional approach relates those flows to the nonlinear Schr\"odinger hierarchy satisfied by the…

Differential Geometry · Mathematics 2018-09-11 Albert Chern , Felix Knöppel , Franz Pedit , Ulrich Pinkall

In this work, we propose a new family of generative flows on an augmented data space, with an aim to improve expressivity without drastically increasing the computational cost of sampling and evaluation of a lower bound on the likelihood.…

Machine Learning · Computer Science 2020-02-19 Chin-Wei Huang , Laurent Dinh , Aaron Courville

We present a novel, conditional generative probabilistic model of set-valued data with a tractable log density. This model is a continuous normalizing flow governed by permutation equivariant dynamics. These dynamics are driven by a…

Normalising flows offer a flexible way of modelling continuous probability distributions. We consider expressiveness, fast inversion and exact Jacobian determinant as three desirable properties a normalising flow should possess. However,…

Machine Learning · Computer Science 2021-10-27 Yumou Wei

We use a novel parameterization of the flowing Hamiltonian to show that the flow equations based on continuous unitary transformations, as proposed by Wegner, can be implemented through a nonlinear partial differential equation involving…

Other Condensed Matter · Physics 2015-06-24 J. N. Kriel , A. Y. Morozov , F. G. Scholtz

The purpose of this paper is to discuss the relationship between commutative and non-commutative integrability of Hamiltonian systems and to construct new examples of integrable geodesic flows on Riemannian manifolds. In particular, we…

Mathematical Physics · Physics 2007-05-23 Alexey V. Bolsinov , Bozidar Jovanovic

Discovering symbolic differential equations from data uncovers fundamental dynamical laws underlying complex systems. However, existing methods often struggle with the vast search space of equations and may produce equations that violate…

Machine Learning · Computer Science 2026-03-11 Jianke Yang , Manu Bhat , Bryan Hu , Yadi Cao , Nima Dehmamy , Robin Walters , Rose Yu

In this study, we introduce novel methodologies designed to adapt original data in response to the dynamics of persistence diagrams along Wasserstein gradient flows. Our research focuses on the development of algorithms that translate…

Algebraic Topology · Mathematics 2024-12-06 Minghua Wang , Jinhui Xu

The Hamiltonian dynamics of a compressible inviscid fluid is formulated as a gauge theory. The idea of gauge equivalence is exploited to unify the study of apparantly distinct physical problems and solutions of new models can be generated…

High Energy Physics - Theory · Physics 2007-05-23 Subir Ghosh

We present a fairly new and comprehensive approach to the study of stationary flows of the Korteweg-de Vries hierarchy. They are obtained by means of a double restriction process from a dynamical system in an infinite number of variables.…

Exactly Solvable and Integrable Systems · Physics 2009-09-25 Gregorio Falqui , Franco Magri , Marco Pedroni , Jorge P. Zubelli

Many equations that arise in a physical context can be posed in the form of a Hamiltonian system, meaning that there is a symplectic structure on an appropriate phase space, and a Hamiltonian functional with respect to which time evolution…

Analysis of PDEs · Mathematics 2017-01-18 Walter Craig