Well posedness and maximum entropy approximation for the dynamics of quantitative traits

Katarína Boďová, Jan Haskovec, Peter A. Markowich

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


We study the Fokker–Planck equation derived in the large system limit of the Markovian process describing the dynamics of quantitative traits. The Fokker–Planck equation is posed on a bounded domain and its transport and diffusion coefficients vanish on the domain’s boundary. We first argue that, despite this degeneracy, the standard no-flux boundary condition is valid. We derive the weak formulation of the problem and prove the existence and uniqueness of its solutions by constructing the corresponding contraction semigroup on a suitable function space. Then, we prove that for the parameter regime with high enough mutation rate the problem exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next, we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt) method for approximation of observables (moments) of the Fokker–Planck solution, which can be interpreted as a nonlinear Galerkin approximation. The limited applicability of the DynMaxEnt method inspires us to introduce its modified version that is valid for the whole range of admissible parameters. Finally, we present several numerical experiments to demonstrate the performance of both the original and modified DynMaxEnt methods. We observe that in the parameter regimes where both methods are valid, the modified one exhibits slightly better approximation properties compared to the original one.
Original languageEnglish (US)
Pages (from-to)108-120
Number of pages13
JournalPhysica D: Nonlinear Phenomena
StatePublished - Nov 6 2017

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): 1000000193
Acknowledgements: We thank Nicholas Barton (IST Austria) for his useful comments and suggestions. JH and PM are funded by KAUST baseline funds and grant no. 1000000193.


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