B09
Structure Preserving Discretization of Gradient Flows
Analyzing Discrete Curves of Steepest Descent in Discrete Energy Landscapes
Many evolution equations from physics, like those for diffusion of dissolved substances or for phase separation in alloys, describe processes in which a system tries to reach the minimum of its energy (or the like) as quickly as possible. The descent towards the minimum is restrained by the system’s inertia. In this project, we discretize these evolution equations by optimizing discrete curves in a discrete energy landscape with respect to a discrete inertia tensor.
 Group: B. Dynamics
 Principal Investigators: Prof. Dr. Oliver Junge, Prof. Dr. Daniel Matthes
 Investigators: Dr. Daniel Karrasch, Benjamin Söllner
 University: TU München
 Term: since 2012
Scientific Details+
The project's objective is to investigate  analytically and numerically  the properties of adapted full discretizations for a class of evolution equations with gradient flow structure. Our motivation is twofold. One goal is to define novel schemes for numerical solution of the evolution equations, that are stable and convergent, and in addition preserve various aspects of the variational structure and the associated qualitative properties of solutions on the discrete level. The second goal is to perform a qualitative analysis, e.g., to study the longtime behaviour, of the resulting dynamical system on a discrete space.
We are mainly interested in the discretization of fluid type equations for mass densities which arise as a steepest descent of an energy or entropy functional in the Wasserstein distance or a related mass transport metric. Specific examples that we intend to study are second order porous medium and fourth order lubrication equations, as well as, in later phases of the project, also more general equations of CahnHilliard type and also genuine Eulerlike hydrodynamic models. Some of the expected advantages of our structure preserving approach in comparison to a "generic" discretization are the following: the potential of the flow will be timemonotone; contraction estimates in the underlying metric will be preserved; and auxiliary Lyapunov functionals for the continuous flow will have discrete counterparts. These properties will also pave the way to proving stability and convergence. On top of that, the discretization will automatically guarantee such general features as nonnegativity of solutions and the conservation of mass.
We plan to explore two different strategies to define adapted discretizations, which we label Lagrangian and Eulerian. The first uses a formulation of the underlying fluid dynamics in a comoving frame. That is, we discretize the evolution of Lagrangian maps rather than the temporal change of the density directly. This approch is wellsuited to gradient flows in the Wasserstein metric, where the Lagrangian map is a concatenation of infinitesimal plans for optimal mass transfer. Our discretization preserves this intuitive geometric interpretation. In the Eulerian approach, which is close to a classical finite element discretization, we will approximate the continuous densities by functions in a finitedimensional ansatz space, e.g., by piecewise constant functions with respect to a fixed decomposition of the spatial domain. For a truely variational approach on these grounds, we will need to design of an efficient method for the calculation of the transportation distance between functions in the ansatz space.
The dynamics of the resulting discrete dynamical system will then be studied  analytically and numerically  in view of the following:
• energy dissipation, Lyapunov functionals, and derivation of discrete a priori estimates;
• qualitative properties of solutions like strict positivity and growth of the support;
• rate of equilibration in the longtime limit;
• existence and stability of special solutions, like quasiselfsimilar profiles;
• convergence of the discrete solutions to a continuous one.
Publications+
Papers

Simon Plazotta.
A BDF2approach for the nonlinear FokkerPlanck equation.
Discrete Contin. Dyn. Syst., 39(5):2893–2913, May 2019.
arXiv:1801.09603, doi:10.3934/dcds.2019120. 
Oliver Junge and Benjamin Söllner.
A convergent Lagrangian discretization for $p$Laplace and fluxlimited diffusion equations.
preprint, 2019.
arXiv:1906.01321. 
Flore Nabet Clément Cancès, Daniel Matthes.
A twophase twofluxes degenerate CahnHilliard model as constrained Wasserstein gradient flow.
Arch. Ration. Mech. Anal., 233(2):837–866, 2019.
arXiv:1712.06446, doi:10.1007/s00205019013696. 
Daniel Matthes and Benjamin Söllner.
Discretization of FluxLimited Gradient Flows: Γconvergence and numerical schemes.
preprint, 2019.
arXiv:1910.09843. 
Julian Fischer and Daniel Matthes.
The waiting time phenomenon in spatially discretized porous medium and thin film equations.
preprint at arXiv, 2019.
arXiv:1911.04185. 
Daniel Matthes and Simon Plazotta.
A Variational Formulation of the BDF2 Method for Metric Gradient Flows.
ESAIM: M2AN, Forthcoming article, July 2018.
doi:10.1051/m2an/2018045. 
Daniel Matthes José A. Carrillo, Bertram Düring and David S. McCormick.
A Lagrangian Scheme for the Solution of Nonlinear Diffusion Equations Using Moving Simplex Meshes.
Journal of Scientific Computing, June 2018, Volume 75, Issue 3, pp 1463–1499, November 2017.
doi:10.1007/s1091501705945. 
Oliver Junge and Ioannis G Kevrekidis.
On the sighting of unicorns: A variational approach to computing invariant sets in dynamical systems.
Chaos: An Interdisciplinary Journal of Nonlinear Science, Nr. 6, Volume 27, June 2017.
doi:10.1063/1.4983468. 
Daniel Matthes and Benjamin Söllner.
Convergent Lagrangian Discretization for DriftDiffusion with Nonlocal Aggregation.
Innovative Algorithms and Analysis pp 313351, March 2017.
doi:10.1007/9783319492629_12. 
Daniel Matthes Oliver Junge and Horst Osberger.
A Fully Discrete Variational Scheme for Solving Nonlinear FokkerPlanck Equations in Multiple Space Dimensions.
SIAM Journal on Numerical Analysis, 55(1):419–443, 2017.
arXiv:1509.07721, doi:10.1137/16M1056560. 
Simon Plazotta and Jonathan Zinsl.
Highfrequency limit of nonautonomous gradient flows of functionals with timeperiodic forcing.
Journal of Differential Equations, Vol. 261, Issue 12, 15 December 2016, Pages 68066855, December 2016.
doi:10.1016/j.jde.2016.09.003. 
Jan Maas and Daniel Matthes.
LongTime Behavior of a Finite Volume Discretization for a Fourth Order Diffusion Equation.
Nonlinearity, Volume 29, Number 7, June 2016.
URL: http://iopscience.iop.org/article/10.1088/09517715/29/7/1992/meta. 
Oliver Junge Andres Denner and Daniel Matthes.
Computing coherent sets using the FokkerPlanck equation.
Journal of Computational Dynamics, 2016, Vol. 3, Issue 2, 2016.
doi:10.3934/jcd.2016008. 
JF Mennemann, D Matthes, RM Weishäupl, and T Langen.
Optimal control of BoseEinstein condensates in three dimensions.
New Journal of Physics, 17(11):113027, November 2015.
URL: http://stacks.iop.org/13672630/17/i=11/a=113027. 
Daniel Matthes and Horst Osberger.
A convergent Lagrangian discretization for a nonlinear fourth order equation.
Found. Comput. Math., 2015. online first.
arXiv:1410.1728. 
Horst Osberger and Daniel Matthes.
Convergence of a Fully Discrete Variational Scheme for a Thin Film Equation.
Radon Series on Computational and Applied Mathematics, 2015. accepted.
arXiv:1509.01513. 
Jonathan Zinsl and Daniel Matthes.
Exponential Convergence to Equilibrium in a Coupled Gradient Flow System Modelling Chemotaxis.
Analysis & PDE, 8(2):425–466, 2015.
arXiv:1310.3977. 
Horst Osberger.
LongTime Behaviour of a Fully Discrete Lagrangian Scheme for a Family of Fourth Order.
Submitted, 2015.
arXiv:1501.04800. 
Jonathan Zinsl and Daniel Matthes.
Transport Distances and Geodesic Convexity for Systems of Degenerate Diffusion Equations.
Calculus of Variations and Partial Differential Equations, 2015. accepted.
arXiv:1409.6520. 
Marco Di Francesco, Massimo Fornasier, JanChristian Hütter, and Daniel Matthes.
Asymptotic Behavior of Gradient Flows Driven by Nonlocal Power Repulsion and Attraction Potentials in One Dimension.
accepted at SIAMMA, January 2014.
arXiv:1401.2338. 
Daniel Matthes and Horst Osberger.
Convergence of a Variational Lagrangian Scheme for a Nonlinear Drift Diffusion Equation.
ESAIM: Mathematical Modelling and Numerical Analysis, 48(03):697–726, 2014. Cambridge Univ Press.
arXiv:1301.0747. 
Jonathan Zinsl.
Geodesically Convex Energies and Confinement of Solutions for a MultiComponent System of Nonlocal Interaction Equations.
Submitted, 2014.
arXiv:1412.3266.
PhD thesis

H. Osberger.
Fully variational Lagrangian discretizations for second and fourth order evolution equations.
Dissertation, Technische Universität München, September 2015.
URL: https://mediatum.ub.tum.de/1271651, dgd:182.
Team+
Prof. Dr. Oliver Junge +
Projects:
B09
University:
TU München
EMail:
oj[at]tum.de
Website: http://wwwm3.ma.tum.de/Allgemeines/OliverJunge
Prof. Dr. Daniel Matthes +
Projects:
B09
University:
TU München
EMail:
matthes[at]ma.tum.de
Website: http://wwwm8.ma.tum.de/personen/matthes/
Dr. Daniel Karrasch +
Projects:
Z,
B09
University:
TU München
EMail:
daniel.karrasch[at]tum.de
Benjamin Söllner +
Projects:
B09
University:
TU München
EMail:
b.soellner[at]ma.tum.de