• The adaptive finite element method 

      [SNAP-2016-013-EN] Gallistl, Dietmar (Mathematisches Forschungsinstitut Oberwolfach, 2016)
      Computer simulations of many physical phenomena rely on approximations by models with a finite number of unknowns. The number of these parameters determines the computational effort needed for the simulation. On the other ...
    • Chaos and chaotic fluid mixing 

      [SNAP-2015-005-EN] Solomon, Tom (Mathematisches Forschungsinstitut Oberwolfach, 2015)
      Very simple mathematical equations can give rise to surprisingly complicated, chaotic dynamics, with behavior that is sensitive to small deviations in the initial conditions. We illustrate this with a single recurrence ...
    • Computational Optimal Transport 

      [SNAP-2017-008-EN] Solomon, Justin (Mathematisches Forschungsinstitut Oberwolfach, 2017-12-21)
      Optimal transport is the mathematical discipline of matching supply to demand while minimizing shipping costs. This matching problem becomes extremely challenging as the quantity of supply and demand points increases; ...
    • Computing the long term evolution of the solar system with geometric numerical integrators 

      [SNAP-2017-009-EN] Fiorelli Vilmart, Shaula; Vilmart, Gilles (Mathematisches Forschungsinstitut Oberwolfach, 2017-12-27)
      Simulating the dynamics of the Sun–Earth–Moon system with a standard algorithm yields a dramatically wrong solution, predicting that the Moon is ejected from its orbit. In contrast, a well chosen algorithm with the ...
    • Darcy's law and groundwater flow modelling 

      [SNAP-2015-007-EN] Schweizer, Ben (Mathematisches Forschungsinstitut Oberwolfach, 2015)
      Formulations of natural phenomena are derived, sometimes, from experimentation and observation. Mathematical methods can be applied to expand on these formulations, and develop them into better models. In the year 1856, ...
    • Data assimilation: mathematics for merging models and data 

      [SNAP-2018-011-EN] Morzfeld, Matthias; Reich, Sebastian (Mathematisches Forschungsinstitut Oberwolfach, 2018-07-10)
      When you describe a physical process, for example, the weather on Earth, or an engineered system, such as a self-driving car, you typically have two sources of information. The first is a mathematical model, and the ...
    • Drugs, herbicides, and numerical simulation 

      [SNAP-2014-010-EN] Benner, Peter; Mena, Hermann; Schneider, René (Mathematisches Forschungsinstitut Oberwolfach, 2014)
      [also available in German] The Colombian government sprays coca fields with herbicides in an effort to reduce drug production. Spray drifts at the Ecuador-Colombia border became an international issue. We developed a ...
    • Fast Solvers for Highly Oscillatory Problems 

      [SNAP-2018-006-EN] Barnett, Alex (Mathematisches Forschungsinstitut Oberwolfach, 2018-06-26)
      Waves of diverse types surround us. Sound, light and other waves, such as microwaves, are crucial for speech, mobile phones, and other communication technologies. Elastic waves propagating through the Earth bounce ...
    • High performance computing on smartphones 

      [SNAP-2016-006-EN] Patera, Anthony T.; Urban, Karsten (Mathematisches Forschungsinstitut Oberwolfach, 2016)
      Nowadays there is a strong demand to simulate even real-world engineering problems on small computing devices with very limited capacity, such as a smartphone. We explain, using a concrete example, how we can obtain a ...
    • Mathematics plays a key role in scientific computing 

      [SNAP-2017-011-EN] Shu, Chi-Wang (Mathematisches Forschungsinstitut Oberwolfach, 2017-12-29)
      I attended a very interesting workshop at the research center MFO in Oberwolfach on “Recent Developments in the Numerics of Nonlinear Hyperbolic Conservation Laws”. The title sounds a bit technical, but in plain language ...
    • Mathematische Modellierung von Krebswachstum 

      [SNAP-2017-004-DE] Engwer, Christian; Knappitsch, Markus (Mathematisches Forschungsinstitut Oberwolfach, 2017-10-17)
      Krebs ist eine der größten Herausforderungen der modernen Medizin. Der WHO zufolge starben 2012 weltweit 8,2 Millionen Menschen an Krebs. Bis heute sind dessen molekulare Mechanismen nur in Teilen verstanden, was eine ...
    • Modeling communication and movement: from cells to animals and humans 

      [SNAP-2015-006-EN] Eftimie, Raluca (Mathematisches Forschungsinstitut Oberwolfach, 2015)
      Communication forms the basis of biological interactions. While the use of a single communication mechanism (for example visual communication) by a species is quite well understood, in nature the majority of species ...
    • Modelling the spread of brain tumours 

      [SNAP-2015-013-EN] Swan, Amanda; Murtha, Albert (Mathematisches Forschungsinstitut Oberwolfach, 2015)
      The study of mathematical biology attempts to use mathematical models to draw useful conclusions about biological systems. Here, we consider the modelling of brain tumour spread with the ultimate goal of improving treatment ...
    • Molecular Quantum Dynamics 

      [SNAP-2017-006-EN] Hagedorn, George A.; Lasser, Caroline (Mathematisches Forschungsinstitut Oberwolfach, 2017-10-24)
      We provide a brief introduction to some basic ideas of Molecular Quantum Dynamics. We discuss the scope, strengths and main applications of this field of science. Finally, we also mention open problems of current ...
    • The mystery of sleeping sickness – why does it keep waking up? 

      [SNAP-2015-015-EN] Funk, Sebastian (Mathematisches Forschungsinstitut Oberwolfach, 2015)
      Sleeping sickness is a neglected tropical disease that affects rural populations in Africa. Deadly when untreated, it is being targeted for elimination through case finding and treatment. Yet, fundamental questions about ...
    • Prony’s method: an old trick for new problems 

      [SNAP-2018-004-EN] Sauer, Tomas (Mathematisches Forschungsinstitut Oberwolfach, 2018-03-06)
      In 1795, French mathematician Gaspard de Prony invented an ingenious trick to solve a recovery problem, aiming at reconstructing functions from their values at given points, which arose from a specific application in ...
    • A short story on optimal transport and its many applications 

      [SNAP-2018-013-EN] Santambrogio, Filippo (Mathematisches Forschungsinstitut Oberwolfach, 2018-08-08)
      We present some examples of optimal transport problems and of applications to different sciences (logistics, economics, image processing, and a little bit of evolution equations) through the crazy story of an industrial ...
    • Swarming robots 

      [SNAP-2016-001-EN] Egerstedt, Magnus (Mathematisches Forschungsinstitut Oberwolfach, 2016)
      When lots of robots come together to form shapes, spread in an area, or move in one direction, their motion has to be planned carefully. We discuss how mathematicians devise strategies to help swarms of robots behave like ...
    • Visual analysis of Spanish male mortality 

      [SNAP-2015-012-ENSNAP-2015-012-DE] Marron, J. S. (Mathematisches Forschungsinstitut Oberwolfach, 2015)
      [also available in German] Statistical visualization uses graphical methods to gain insights from data. Here we show how a technique called principal component analysis is used to analyze mortality in Spain over about the ...
    • Wie steuert man einen Kran? 

      [SNAP-2016-007-DE] Altmann, Robert; Heiland, Jan (Mathematisches Forschungsinstitut Oberwolfach, 2016)
      Die Steuerung einer Last an einem Kran ist ein technisch und mathematisch schwieriges Problem, da die Bewegung der Last nur indirekt beeinflusst werden kann. Anhand eines Masse-Feder-Systems illustrieren wir diese ...