2020
DOI: 10.1007/978-3-030-43651-3_16
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TPFA Finite Volume Approximation of Wasserstein Gradient Flows

Abstract: Numerous infinite dimensional dynamical systems arising in different fields have been shown to exhibit a gradient flow structure in the Wasserstein space. We construct Two Point Flux Approximation Finite Volume schemes to discretize these problems preserving their variational structure and obtaining second order accuracy in space. The choice of the discrete solver plays an important role in designing these schemes for robustness purposes. We present two applications to test the scheme and show its order of con… Show more

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Cited by 3 publications
(9 citation statements)
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“…The fundamental tool is the solution of JKO steps, which requires the expensive problem of computing the Wasserstein distance. Following [12,30], we linearize the Wasserstein distance obtaining LJKO steps, a more affordable problem to solve. Remarkably, this approach preserves the second order accuracy in time of our time discretization.…”
Section: Finite Volume Discretizationmentioning
confidence: 99%
See 2 more Smart Citations
“…The fundamental tool is the solution of JKO steps, which requires the expensive problem of computing the Wasserstein distance. Following [12,30], we linearize the Wasserstein distance obtaining LJKO steps, a more affordable problem to solve. Remarkably, this approach preserves the second order accuracy in time of our time discretization.…”
Section: Finite Volume Discretizationmentioning
confidence: 99%
“…2 ), both leading to second order accurate schemes in space [30]. The former choice is possible only if x K ∈ K, which may not be always the case for arbitrary admissible meshes.…”
Section: Finite Volume Discretizationmentioning
confidence: 99%
See 1 more Smart Citation
“…On the other hand, using the arithmetic interpolation, I (r, s) = (r + s)/2, would not work directly since the solutions may become negative. In this case additional technical steps, like a Lagrange multiplicator as in [39], are necessary to obtain the evolution of a non-negative probability density. We use the more physical inspired upwind flux, which automatically ensures the positivity of the density.…”
Section: Graph Setting With General Interactionsmentioning
confidence: 99%
“…The perturbation introduced by the barrier function can be tuned by multiplying it by a positive coefficient µ and the original solution is recovered via a continuation method for µ going to zero. The final algorithm is robust and can be easily generalized to similar problems (for example, we have already applied it successfully in [25] for the solution of Wasserstein gradient flows).…”
Section: Numerical Solutionmentioning
confidence: 99%