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Research Interestsoptimal transport
stochastic mass transfer, martingale optimal transport, causal transport
matching and allocation problems
robust finance
random measures, point processes
Project membership
Mathematics Münster

C: Models and Approximations

C1: Evolution and asymptotics
Current PublicationsBackhoff-Veraguas J, Beiglböck M, Huesmann M, Källblad S Martingale Benamou-Brenier: a probabilistic perspective. Ann. Probab. Vol. 48 (5), 2020 online
Beiglböck M, Cox AMG, Huesmann M The geometry of multi-marginal Skorokhod Embedding. Probability Theory and Related Fields Vol. 176, 2020 online
Huesmann M, Trevisan D A Benamou-Brenier formulation of martingale optimal transport. Bernoulli Vol. 25 (4A), 2019, pp 2729-2757 online
Huesmann M, Stebegg F Monotonicity preserving transformations of MOT and SEP. Stochastic Processes and their Applications Vol. 128 (4), 2018, pp 1114-1134 online
Current ProjectsEXC 2044 - C1: Evolution and asymptotics In this unit, we will use generalisations of optimal transport metrics to develop gradient flow descriptions of (cross)-diffusion-reaction systems, rigorously analyse their pattern forming properties, and develop corresponding efficient numerical schemes. Related transport-type- and hyperbolic systems will be compared with respect to their pattern-forming behaviour, especially when mass is conserved. Bifurcations and the effects of noise perturbations will be explored.

Moreover, we aim to understand defect structures, their stability and their interactions. Examples are the evolution of fractures in brittle materials and of vortices in fluids. Our analysis will explore the underlying geometry of defect dynamics such as gradient descents or Hamiltonian structures. Also, we will further develop continuum mechanics and asymptotic descriptions for multiple bodies which deform, divide, move, and dynamically attach to each other in order to better describe the bio-mechanics of growing and dividing soft tissues.

Finally, we are interested in the asymptotic analysis of various random structures as the size or the dimension of the structure goes to infinity. More specifically, we shall consider random polytopes and random trees.For random polytopes we would like to compute the expected number of faces in all dimensions, the expected (intrinsic) volume, and absorption probabilities, as well as higher moments and limit distributions for these quantities. online
E-Mailmartin dot huesmann at uni-muenster dot de
Phone+49 251 83-35086
FAX+49 251 83-32712
Secretary   Sekretariat Kollwitz
Frau Anita Kollwitz
Telefon +49 251 83-33770
Fax +49 251 83-32712
Zimmer 130.030
AddressProf. Dr. Martin Huesmann
Institut für Mathematische Stochastik
Fachbereich Mathematik und Informatik der Universität Münster
Orléans-Ring 10
48149 Münster
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