SFB Colloquium Guest Talk Abstract - 2018 - Faranda

Davide Faranda, LSCE (Laboratoire des Sciences du Climat et de l’Environnement), CNRS, Paris-Saclay

Computation and characterisation of local subfilter-scale energy transfer in atmospheric flows

Atmospheric motions are governed by turbulent motions associated to nontrivial energy transfers at small scales (direct cascade) and/or at large scales (inverse cascade). Although it is known that the two cascades coexist, energy fluxes have been previously investigated from the spectral point of view but not on their instantaneous spatial and local structure. Here, we compute local and instantaneous subfilter-scale energy transfers in two sets of reanalyses (NCEP–NCAR and ERA-Interim) in the troposphere and the lower stratosphere for the year 2005. The fluxes are mostly positive (toward subgrid scales) in the troposphere and negative in the stratosphere, reflecting the baroclinic and barotropic nature of the motions, respectively. The most intense positive energy fluxes are found in the troposphere and are associated with baroclinic eddies or tropical cyclones. The computation of such fluxes can be used to characterize the amount of energy lost or missing at the smallest scales in climate and weather models.

SFB Colloquium Guest Talk Abstract - 2018 - Giannakis

Dimitris Giannakis, Courant Institute

Data-driven approaches for spectral decomposition of ergodic dynamical systems

We discuss techniques for approximating the spectra of Koopman operators governing the evolution of observables in ergodic dynamical systems. These methods are based on representations of Koopman operators in bases for appropriate Hilbert spaces of observables learned from time-ordered measurements of the system using kernel algorithms for machine learning. We establish spectral convergence results for the point spectrum, and present regularization approaches applicable to systems with continuous spectra. We illustrate this framework with applications to toy dynamical systems and climate data.

SFB Colloquium Guest Talk Abstract - 2018 - Rogal

Jutta Rogal, Ruhr-Universität Bochum

Extended timescale simulations of atomistic processes during phase transformations in materials

Obtaining atomistic insight into the fundamental processes during phase transformations and their dynamical evolution up to experimental timescales remains one of the great challenges in materials modelling. In particular, if the mechanisms of the phase transformations are governed by so-called rare events the timescales of interest will reach far beyond the applicability of regular molecular dynamics simulations. In addition to the timescale problem the simulations provide a vast amount of data in the high-dimensional phase space. A physical interpretation of these data requires the projection into a low-dimensional space and the identification of suitable reaction coordinates.

In this presentation, I will give an overview of our recent progress in the application of advanced atomistic simulation techniques to capture the dynamical behaviour during phase transformations over a large range of timescales. One of the key results is the analysis of nucleation and growth mechanisms that can be extracted from the simulation data. By applying a likelihood maximisation scheme the quality of different reaction coordinates is evaluated which enables us to identify the most important order parameters that characterise the atomistic transformation processes.


SFB Colloquium Talk Abstract - 2018 - Sullivan

Tim Sullivan, Zuse Institut Berlin

"What is .. a well-posed Bayesian inverse problem?"

Inverse problems, meaning the recovery of states or parameters in a mathematical model that match some observed data, are ubiquitous in applied sciences. They are also prime examples of ill-posed problems in the sense of Hadamard: either there is no solution in the strict sense, or there are multiple solutions, or the solution(s) depend sensitively upon the observed data and other parts of the problem specification. Regularisation of the inverse problem, whether deterministic or Bayesian, is intended to overcome these difficulties. This "What is...?" talk will outline the mathematical theory of well-posed Bayesian inverse problems for continuum quantities, exemplified by PDE-constrained inverse problems, as advanced by Andrew Stuart and collaborators over the last decade.


SFB Colloquium Guest Talk Abstract - 2018 - Kanaan

Samir Kanaan, Universitat Politécnica de Catalunya

Multiview data: what, why, and how

Most pattern recognition methods are designed to process data inputs from a single source. Therefore, they are not well equipped to deal with data inputs from several, possibly heterogeneous sources. However, in real life applications it is often the case that there are several sources available. In the classical data processing pipeline there are two options: to stack all the data together, with potential data coherence problems, or to discard some of the data sources. None of these options extracts the full potential of the data available. Multiview pattern recognition methods are designed to tackle with such multiple source datasets, processing each data source as a independent input while merging all the relevant information into a single result. This talk is an introduction to multiview data, possible multiview aspects and applications, and the associated multiview pattern recognition methods in the state of the art, as well as the differences between the classical, single-view data processing pipeline and a multiview data processing pipeline.

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