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Gradient flows are a powerful tool for optimizing functionals in general metric spaces, including the space of probabilities endowed with the Wasserstein metric. A typical approach to solving this optimization problem relies on its…

Machine Learning · Statistics 2021-12-02 David Alvarez-Melis , Yair Schiff , Youssef Mroueh

Gradient-flow (GF) viewpoints unify and illuminate optimization algorithms, yet most GF analyses focus on unconstrained settings. We develop a geometry-respecting framework for constrained problems by (i) reparameterizing feasible sets with…

Optimization and Control · Mathematics 2025-08-29 Valentin Leplat

We present a short overview on the strongest variational formulation for gradient flows of geodesically $\lambda$-convex functionals in metric spaces, with applications to diffusion equations in Wasserstein spaces of probability measures.…

Classical Analysis and ODEs · Mathematics 2010-09-21 Sara Daneri , Giuseppe Savaré

Assuming a-priori a smooth generating vector field, we introduce a generally covariant measure of the flow geometry called the referential gradient of the flow. The main result is the explicit relation between the referential gradient and…

Mathematical Physics · Physics 2014-11-21 J. K. Edmondson

We consider some elementary aspects of the geometry of the space of probability measures endowed with Wasserstein distance. In such a setting, we discuss the various terms entering Perelman's shrinker entropy, and characterize two new…

Differential Geometry · Mathematics 2008-01-24 Mauro Carfora

Michor and Mumford showed that the mean curvature flow is a gradient flow on a Riemannian structure with a degenerate geodesic distance. It is also known to destroy the uniform density of gridpoints on the evolving surfaces. We introduce a…

Analysis of PDEs · Mathematics 2018-09-18 Wenhui Shi , Dmitry Vorotnikov

The one-way measurement model is a framework for universal quantum computation, in which algorithms are partially described by a graph G of entanglement relations on a collection of qubits. A sufficient condition for an algorithm to perform…

Quantum Physics · Physics 2008-03-01 Niel de Beaudrap

Recently, the impressive empirical success of policy gradient (PG) methods has catalyzed the development of their theoretical foundations. Despite the huge efforts directed at the design of efficient stochastic PG-type algorithms, the…

Machine Learning · Computer Science 2023-11-09 Ilyas Fatkhullin , Anas Barakat , Anastasia Kireeva , Niao He

Whenever an It\^o-Wentsel type of formula holds for composition of flows of a certain differential dynamics, there exists locally a decomposition of the corresponding flow according to complementary distributions (or foliations, in the case…

Probability · Mathematics 2022-12-20 Pedro Catuogno , Lourival Lima , Paulo Ruffino

We investigate the second-order R\'enyi entanglement entropy at the quantum critical point of a spin-1/2 antiferromagnetic Heisenberg model on a columnar dimerized square lattice. The universal constant $\gamma$ in the area-law scaling…

Statistical Mechanics · Physics 2026-05-07 Zhiyan Wang , Zhe Wang , Yi-Ming Ding , Zenan Liu , Zheng Yan , Long Zhang

This work consists an introduction to the classical and quantum information theory of geometric flows of (relativistic) Lagrange--Hamilton mechanical systems. Basic geometric and physical properties of the canonical nonholonomic…

General Physics · Physics 2020-07-27 Sergiu I. Vacaru

This article is concerned with the existence of nonnegative weak solutions to a particular fourth-order partial differential equation: it is a formal gradient flow with respect to a generalized Wasserstein transportation distance with…

Analysis of PDEs · Mathematics 2016-03-07 Jonathan Zinsl

Wasserstein gradient flows (WGFs) describe the evolution of probability distributions in Wasserstein space as steepest descent dynamics for a free energy functional. Computing the full path from an arbitrary initial distribution to…

Machine Learning · Computer Science 2026-04-14 Chengyu Liu , Xiang Zhou

Using jointly geometric and stochastic reformulations of nonconvex problems and exploiting a Monge-Kantorovich gradient system formulation with vanishing forces, we formally extend the simulated annealing method to a wide class of global…

Analysis of PDEs · Mathematics 2022-04-05 Jérôme Bolte , Laurent Miclo , Stéphane Villeneuve

This paper introduces new methods to study the long time behaviour of the generalised gradient flow associated with a solution of the critical equation for mechanical Hamiltonian system posed on the flat torus $\mathbb{T}^d$. For this…

Analysis of PDEs · Mathematics 2025-09-01 Paolo Albano , Piermarco Cannarsa , Wei Cheng , Cristian Mendico

We study second-order hydrodynamic transport in strongly coupled non-conformal field theories with holographic gravity duals in asymptotically anti-de Sitter space. We first derive new Kubo formulae for five second-order transport…

High Energy Physics - Theory · Physics 2017-03-28 Philipp Kleinert , Jonas Probst

We study the equation of one-dimensional quasistatic nonlinear viscoelasticity with Dirichlet boundary conditions, in the particular case that the underlying dissipation geometry (provided by the viscosity) is comparable to the Bhattacharya…

Analysis of PDEs · Mathematics 2026-05-12 Alexander Mielke , Billy Sumners

On a compact Riemannian manifold, we study the various dynamical properties of the Schr\"odinger flow $(e^{it\Delta/2})$, through the notion of semiclassical measures and the quantum-classical correspondence between the Schr\"odinger…

Analysis of PDEs · Mathematics 2011-10-11 Nalini Anantharaman , Fabricio Macia

While in classical turbulence helicity depletes nonlinearity and can alter the evolution of turbulent flows, in quantum turbulence its role is not fully understood. We present numerical simulations of the free decay of a helical quantum…

Fluid Dynamics · Physics 2017-06-28 P. Clark di Leoni , P. D. Mininni , M. E. Brachet

We prove the correspondence between the solutions of the sub-elliptic heat equation in a Carnot group $\mathbb{G}$ and the gradient flows of the relative entropy functional in the Wasserstein space of probability measures on $\mathbb{G}$.…

Differential Geometry · Mathematics 2023-09-07 Luigi Ambrosio , Giorgio Stefani
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