256 research outputs found
Entropic Wasserstein Gradient Flows
This article details a novel numerical scheme to approximate gradient flows
for optimal transport (i.e. Wasserstein) metrics. These flows have proved
useful to tackle theoretically and numerically non-linear diffusion equations
that model for instance porous media or crowd evolutions. These gradient flows
define a suitable notion of weak solutions for these evolutions and they can be
approximated in a stable way using discrete flows. These discrete flows are
implicit Euler time stepping according to the Wasserstein metric. A bottleneck
of these approaches is the high computational load induced by the resolution of
each step. Indeed, this corresponds to the resolution of a convex optimization
problem involving a Wasserstein distance to the previous iterate. Following
several recent works on the approximation of Wasserstein distances, we consider
a discrete flow induced by an entropic regularization of the transportation
coupling. This entropic regularization allows one to trade the initial
Wasserstein fidelity term for a Kulback-Leibler divergence, which is easier to
deal with numerically. We show how KL proximal schemes, and in particular
Dykstra's algorithm, can be used to compute each step of the regularized flow.
The resulting algorithm is both fast, parallelizable and versatile, because it
only requires multiplications by a Gibbs kernel. On Euclidean domains
discretized on an uniform grid, this corresponds to a linear filtering (for
instance a Gaussian filtering when is the squared Euclidean distance) which
can be computed in nearly linear time. On more general domains, such as
(possibly non-convex) shapes or on manifolds discretized by a triangular mesh,
following a recently proposed numerical scheme for optimal transport, this
Gibbs kernel multiplication is approximated by a short-time heat diffusion
Similarity Solutions for a Steady MHD Falkner-Skan Flow and Heat Transfer over a Wedge Considering the Effects of Variable Viscosity and Thermal Conductivity
An analysis is carried out to study the Falkner–Skan flow and heat transfer of an incompressible, electrically conducting fluid over a wedge in the presence of variable viscosity and thermal conductivity effects. The similarity solutions are obtained using scaling group of transformations. Furthermore the similarity equations are solved numerically by employing Kellr-Box method. Numerical results of the local skin friction coefficient and the local Nusselt number as well as the velocity and the temperature profiles are presented for different physical parameters
Courbure discrète : théorie et applications
International audienceThe present volume contains the proceedings of the 2013 Meeting on discrete curvature, held at CIRM, Luminy, France. The aim of this meeting was to bring together researchers from various backgrounds, ranging from mathematics to computer science, with a focus on both theory and applications. With 27 invited talks and 8 posters, the conference attracted 70 researchers from all over the world. The challenge of finding a common ground on the topic of discrete curvature was met with success, and these proceedings are a testimony of this wor
Variational Methods for Evolution (hybrid meeting)
Variational principles for evolutionary systems take advantage of the rich toolbox provided by the theory of the calculus of variations. Such principles are available for Hamiltonian systems in classical mechanics, gradient flows for dissipative systems, but also time-incremental minimization techniques for more general evolutionary problems. The new challenges arise via the interplay of two or more functionals (e.g. a free energy and a dissipation potential), new structures (systems with nonlocal transport, gradient flows on graphs, kinetic equations, systems of equations)
thus encompassing a large variety of applications in the modeling of materials and fluids, in biology, in multi-agent systems, and in data science.
This workshop brought together a broad spectrum of researchers from
calculus of variations, partial differential equations, metric
geometry, and stochastics, as well as applied and computational
scientists to discuss and exchange ideas. It focused on variational
tools such as minimizing movement schemes,
optimal transport, gradient flows, and large-deviation principles for
time-continuous Markov processes, -convergence and homogenization
Consistency and convergence for a family of finite volume discretizations of the Fokker--Planck operator
We introduce a family of various finite volume discretization schemes for the
Fokker--Planck operator, which are characterized by different weight functions
on the edges. This family particularly includes the well-established
Scharfetter--Gummel discretization as well as the recently developed
square-root approximation (SQRA) scheme. We motivate this family of
discretizations both from the numerical and the modeling point of view and
provide a uniform consistency and error analysis. Our main results state that
the convergence order primarily depends on the quality of the mesh and in
second place on the quality of the weights. We show by numerical experiments
that for small gradients the choice of the optimal representative of the
discretization family is highly non-trivial while for large gradients the
Scharfetter--Gummel scheme stands out compared to the others
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