# Scientific Computing seminar at CWI Amsterdam

*Organizers: Svetlana Dubinkina (SC) and Enrico Camporeale (MD).*

## Upcoming

Tuesday 22 May 2018

Time: 15.00hrs

Room: L016

Speaker: Jean Francois Rippoll (CEA, Paris)

Thursday 7 June 2018

Time: 11.00hrs

Room: L120

Speaker: guest of Benjamin from Shell

Tuesday 19 June 2018

Time: 15.00hrs

Room: L120

Speaker: Alfons Hoekstra (UvA)

## Past

Tuesday 8 May 2018

Time: 15.00hrs

Room: L102

Speaker: Nikos Rekatsinas (UvA)

Title: Adaptive Wavelet Methods for solving First Order System Least Squares

Abstract: We discuss Adaptive Wavelet Galerkin Methods (awgm) for the optimal adaptive solution of variational formulations of stationary, and evolutionary PDEs. Adaptive approximation allows the local resolution of the approximation space to be adjusted to the local smoothness of the solution. Optimality of the solution means it can be approximated at the best possible rate allowed by the basis -being in our case a wavelet Riesz basis- in optimal computational complexity. At first we show that any well-posed 2nd order PDE can be reformulated as a well-posed first order system least squares (FOSLS) problem, which we subsequently solve using the awgm. On this ground we design a novel, more efficient approximate residual evaluation scheme that improves the overall quantitative properties of the awgm. As an alternative to the usual time-marching schemes, which are not suited to efficiently approximate singularities that are local in both space and time, we extend our approach to the optimal adaptive solution of simultaneous space-time variational formulations of parabolic evolutionary PDEs. The use of tensor products of temporal and spatial wavelets allows for the whole time evolution problem to be solved at a complexity of solving one instance of the corresponding stationary problem. We illustrate our findings with numerical results. The talk is based on joint work with Rob Stevenson (KdVI, Amsterdam).

Tuesday 24 April 2018

Time: 15.00hrs

Room: L120

Speaker: Bastiaan Braams (Multiscale Dynamics, CWI)

Title: Potential energy surfaces for molecular modelling

Abstract: Potential energy surfaces represent the total energy of a system of nuclei and electrons as a function of the nuclear configuration. These surfaces (and property surfaces, such as the dipole moment) are key tools for quasi-classical trajectory calculations, molecular spectroscopy, quantum scattering and other applications in molecular science. In the talk I will first describe methods developed and used in collaboration with Joel Bowman (Emory University) to fit full-dimensional potential energy and dipole moment surfaces for small molecules and molecular reaction complexes, with up to about eight nuclei depending on the application. The methods take full account of permutational symmetry among like nuclei, and this required extensive use of computer algebra through the Magma system. I will follow up with discussion of areas for future work, including the treatment of electronic excited states, and of the need for high quality potential energy surfaces for studies of plasma-material interaction.

Date: Tuesday 10 April 2018

Time: 15.00hrs

Room: L120

Speaker: Carl Shneider (UMC Utrecht)

Title: A machine learning method to find mutations in the human genome

Abstract: In this talk I will discuss a deep learning neural network methodology to detect somatic mutations in whole genome sequencing data of cancer patients.

Date: Tuesday 27 March 2018

Time: 15.00hrs

Room: L120

Speaker: Sarah Gaaf (UU)

Title: Projection techniques for problems involving large-scale matrix equations

Abstract: I would like to discuss various iterative procedures for problems involving large-scale Sylvester equations. I will treat two interesting sub problems: (1) Consider the Sylvester equation AX - XB = C. An important issue when solving this matrix equation is the sensitivity of the solution X to perturbations in the matrices A, B, C. It turns out that the sensitivity is inversely proportional to the separation between the matrices A and B. How to compute this quantity for large-scale problems will be addressed in this talk. (2) Consider a more general Sylvester type of equation, a system of linear matrix equations: AX + YB = C, DX + YE = F. I will first introduce an algorithm to solve the small-scale problem. Then I will show how to develop an iterative method for the problem when the matrices involved are large and sparse.

Date: Tuesday 27 February 2018

Time: 11.00hrs

Room: L120

Speaker: Lisanne Rens (Scientific Computing, CWI)

Title: Mathematical biology of cell-extracellular matrix interactions during morphogenesis

Abstract: Morphogenesis, the shaping of organisms, organs and tissues is driven by chemical signals and physical forces. It is still poorly understood how cells are able to collectively form intricate patterns, like for instance vascular networks. In particular, we were concerned with how interactions between the cell and the extracellular matrix (a protein network surrounding tissues that supports cells and guides cell migration) regulates morphogenesis. My PhD has mainly focused on how physical forces may drive morphogenesis. Lab experiments have shown that the mechanical properties of the matrix, such as its stiffness, regulate morphogenesis. In this presentation I will focus on my work on mechanical cell-matrix interactions. We developed a multiscale model that describe cells and the matrix and their interactions through physical forces. In this model, cells are represented by the Cellular Potts Model. The deformations in the ECM are calculated using a Finite Element Method. We model a mechanical feedback between cells and the ECM, where 1) cells pull on the ECM, 2) strains are generated in the ECM, and 3) cells preferentially extend protrusions oriented with strain. Similar to lab experiments, simulations show that cells are able to generate vascular like patterns on matrices of intermediate stiffness. Lab experiments where the matrix is uniaxially stretched, show that cells orient parallel to stretch. Model results on cells on a stretched matrices with and without traction forces indicate that cell traction forces amplify cell orientation parallel to stretch. Furthermore, they allow cells to organize into strings in the direction of stretch. I will also show an extension of this model. Stiffness sensing is mediated by transmembrane integrin molecules, which behave as 'catch bonds' whose strength increases under tension. Focal adhesions, which are large assemblies of these integrins, grow larger on stiffer substrates. We included such dynamics in our multiscale model. This second model explains how cell shape depends on matrix stiffness and how cells are able to durotact (move up a stiffness gradient). This model gives a more molecular understanding of how cells respond to matrix stiffness.

Date: Tuesday 13 February 2018

Time: 15.00hrs

Room: L120

Speaker: Jeroen Vink (Shell Projects & Technology)

Title: Challenges for History Matching and Uncertainty Quantification in Subsurface Flow modelling

Abstract: For oil and gas companies, it always has been, and still is a major challenge to design and implement integrated modeling workflows that properly capture all relevant subsurface features, including their uncertainties. In this talk I will discuss the two main challenges facing any workflow for assisted history matching and uncertainty quantification: it has to be sufficiently simple and computationally efficient that it can be used routinely throughout the company, and it has to be sufficiently accurate and robust that it truly improves field development forecasts and plans. I will explain why Bayesian-style uncertainty quantification, which is typically applied to account for the impact of data on forecast uncertainty, can easily lead to wrong results. Interestingly, it can then be argued that the adjustments required to fix this problem, allow using a simplifying approximation to incorporate the constraints of field data on forecast uncertainty. This opens up opportunities to develop new strategies and methods, such as the “Gaussian Mixture Model” method, to achieve credible uncertainty quantification.

Date: Tuesday 23 January 2018

Time: 15.00hrs

Room: L120

Speaker: Enrico Colizzi (Scientific Computing, CWI)

Title: Multilevel Evolution in the RNA world

Abstract: In modern life, DNA stores genetic information and proteins perform most of the functions needed in a cell. This separation between information and function was not present before the origin of life. The "RNA world hypothesis" states that about four billion years ago a single molecular species - an RNA-like polymer - both carried information as well as catalysed chemical reactions. Much work has been done in the past 50 years around one fundamental question: How does such world evolve (by mutation and selection) to larger complexity and, ultimately, to modern life?

In this talk I will briefly introduce the classical theoretical work on evolutionary dynamics in the RNA world. I will then discuss some work (including mine) on spatial self-organisation and multilevel evolution in more details. I will finish by presenting some questions about pre-biotic evolution that are still open, but amenable to investigation.

Date: Tuesday 5th December 2017

Time: 15.00hrs

Room: L120

Speaker: Michael S. F. Kirk (NASA Goddard Space Flight Center / Catholic University of America)

Title: Poisson-Gaussian Noise Modeling in Solar Images

Abstract: All digital images are corrupted by noise. In most solar imaging, we have the luxury of high photon counts and low background contamination, which when combined with carful calibration, minimize much of the impact noise has on the measurement. Outside high-intensity regions, such as in coronal holes, the noise component can become significant and complicate feature recognition and segmentation. We create a practical estimate of noise in the Solar Dynamics Observatory’s Atmospheric Imaging Assembly (SDO AIA) images across the detector CCD. A Poisson-Gaussian model of noise is well suited in the digital imaging environment due to the statistical distributions of photons and the characteristics of the CCD. Using the dark and flat field calibration images, the level-1 AIA images, and readout noise measurements, we construct a maximum-a-posteriori estimation of the expected error in the AIA images. These estimations of noise not only provide a clearer view of solar features in AIA, but they are also relevant to error characterizations of other solar images.

Date: Friday 10th November 2017

Time: 15.00hrs

Room: L120

Speaker: David K. Lubensky (University of Michigan, USA)

Title: Self-organization, planar polarity, and tissuehttps://www.cwi.nl/research/groups/scientific-computing response to mechanical stress: From fish to fibers

Abstract: The orderly packing and precise arrangement of epithelial cells is essential to the functioning of many tissues, and refinement of this packing during development is a central theme in animal morphogenesis. The mechanisms that determine epithelial cell shape and position, however, remain incompletely understood. Here, I will use a striking example of planar order in an epithelium--the periodic, almost crystalline distribution of cone photoreceptors in the adult teleost fish--as an inspiration for considering some broader theoretical issues related to cell packings. First, based on observations of the emergence of photoreceptor packing near the retinal margin, I will propose a phenomenological mathematical model in which ordered columns of cells form as a result of coupling between planar cell polarity (PCP) and anisotropic tissue-scale mechanical stresses. This model correctly predicts a number of features of cell packing in mutant and regenerated retinas. The model also turns out to have rich repertoire of behaviors with implications for other developmental systems. I will briefly consider two of these behaviors: Spontaneous left-right symmetry breaking and the formation of supracellular actin cables in response to applied stress. Unexpectedly, the latter phenomenon depends sensitively on fairly subtle statistical features of the packing topology; I will illustrate this dependence numerically and with some preliminary experimental results from *Drosophila *development.

Date: Tuesday 20th June 2017

Time: 15.00hrs

Room: L120

Speaker: Jeroen Wouters (University of Reading, UK)

Title: Computation of extreme heat waves in climate models using a rare event simulation algorithm

Abstract: Studying extreme events and how they evolve in a changing climate is one of the most important current scientific challenges. Starting from complex climate models, a key difficulty is to be able to run long enough simulations in order to observe those extremely rare events. In physics, chemistry, and biology, rare event simulation algorithms have recently been developed to compute probabilities of events that cannot be observed in direct numerical simulations. Here we propose such an algorithm, applied to extreme heat or cold waves, based on statistical physics approaches. This algorithm yields an improvement of more than two orders of magnitude in the sampling efficiency. We describe dynamics of events that would not be observed otherwise. We show that European extreme heat waves are related to a global teleconnection pattern involving Greenland and Russia. This is a joint work with Francesco Ragone (University of Milano–Bicocca) and Freddy Bouchet (ENS Lyon).

Date: Tuesday 13th June 2017

Time: 15.00hrs

Room: L120

Speaker: Xiaozhe Hu (Tufts University, Medford, US)

Title: Robust Preconditioners for Coupled Problems

Abstract: Many mathematical models in physics, engineering, biology, and other fields are governed by coupled systems of partial differential equations (PDEs). An essential component, and usually the most time-consuming part of simulating coupled PDEs, is solving the large-scale and ill-conditioned linear systems of equations arising from the linearization and discretization of the PDEs. In this work, we generalize and improve the traditional framework of preconditioners on saddle point systems for several practical applications, including poromechanics and magnetohydrodynamics. We show that the new preconditioners are robust with respect to certain physical and discretization parameters and preserve important physical laws if necessary. Preliminary numerical experiments are presented to support the theory and demonstrate the robustness of our algorithms. This is joint work with James Adler (Tufts), Francisco Gaspar (CWI), Carmen Rodrigo (University of Zaragoza), Jinchao Xu and Ludmil Zikatanov (Penn State).

Date: Tuesday 28th February 2017

Time: 15.00hrs

Room: L120

Speaker: Stephen Smith (Life Sciences, University of Edinburgh)

Title: Efficiently simulating the crowded cytoplasm

Brownian dynamics simulations are an increasingly popular tool for understanding spatially-extended biochemical reaction systems. Recent improvements in our understanding of the cellular environment show that volume exclusion and crowding effects are fundamental to reaction networks inside cells. These systems are frequently studied by incorporating inert hard spheres (crowders) into three-dimensional Brownian dynamics simulations, however these methods are extremely slow owing to the sheer number of possible collisions between particles. We propose a rigorous "crowder-free" method to dramatically increase simulation speed for crowded biochemical reaction systems by eliminating the need to explicitly simulate the crowders. We consider both the case where the reactive particles are point particles, and where they themselves occupy a volume. Using simulations of simple chemical reaction networks we show that the "crowder-free" method is up to three orders of magnitude faster than conventional BD and yet leads to nearly-indistinguishable results from the latter.

Date: Tuesday 7th February 2017

Time: 15.00hrs

Room: L120

Speaker: Alef Sterk (RU Groningen)

Title: On the predictability of extremes: does the butterfly effect ever decrease?

Abstract: This study investigates whether or not predictability always decreases for more extreme events. Predictability is measured by the Mean Squared Error (MSE), estimated here from the difference of pairs of ensemble forecasts, conditioned on one of the forecast variables (the “pseudo-observation”) exceeding a threshold.

Using an exchangeable linear regression model for pairs of forecast variables, we show that the MSE can be decomposed into the sum of three terms: a threshold-independent constant, a mean term that always increases with threshold, and a variance term that can either increase, decrease, or stay constant with threshold. Using the Generalised Pareto Distribution to model wind speed excesses over a threshold, we show that MSE always increases with threshold at sufficiently high threshold. However, MSE can be a decreasing function of threshold at lower thresholds but only if the forecasts have finite upper bounds.

The methods are illustrated by application to daily wind speed forecasts for London made using the 24 member Met Office Global and Regional Ensemble Prediction System from 1 Jan 2009 to 31 May 2011. For this example, the mean term increases faster than the variance term decreases with increasing threshold, and so predictability decreases for more extreme events.

This is joint work with David Stephenson, Mark Holland, and Ken Mylne.

Date: Wednesday 18th January 2017

Time: 15.00hrs

Room: L120

Speaker: Joris Bierkens (TU Delft)

Title: The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data

Abstract: Standard MCMC methods can scale poorly to big data settings due to the need to evaluate the likelihood at each iteration. There have been a number of approximate MCMC algorithms that use sub-sampling ideas to reduce this computational burden, but with the drawback that these algorithms no longer target the true posterior distribution. We introduce a new family of Monte Carlo methods based upon a multi-dimensional version of the Zig-Zag process of (Bierkens, Roberts, 2016), a continuous time piecewise deterministic Markov process. While traditional MCMC methods are reversible by construction the Zig-Zag process offers a flexible non-reversible alternative. The dynamics of the Zig-Zag process correspond to a constant velocity model, with the velocity of the process switching at events from a point process. The rate of this point process can be related to the invariant distribution of the process. If we wish to target a given posterior distribution, then rates need to be set equal to the gradient of the log of the posterior. Unlike traditional MCMC, We show how the Zig-Zag process can be simulated without discretisation error, and give conditions for the process to be ergodic. Most importantly, we introduce a sub-sampling version of the Zig-Zag process that is an example of an exact approximate scheme. That is, if we replace the true gradient of the log posterior with an unbiased estimator, obtained by sub-sampling, then the resulting approximate process still has the posterior as its stationary distribution. Furthermore, if we use a control-variate idea to reduce the variance of our unbiased estimator, then both heuristic arguments and empirical observations show that Zig-Zag can be super-efficient: after an initial pre-processing step, essentially independent samples from the posterior distribution are obtained at a computational cost which does not depend on the size of the data.

Date: Tuesday 20th December 2016

Time: 15.00hrs

Room: L120

Speaker: Gemma Colldeforns (CRM, Barcelona)

Title: Wavelets for quantifying credit risk portfolio losses under multi-factor models

Abstract: We compute tail probability, Value at Risk and Expected Shortfall risk measures of the portfolio credit risk problem under multi-factor Gaussian and t-copula scenarios. To do so, we depart from the characteristic function of the portfolio density and we use a wavelet Fourier inversion method to recover it.

Date: Tuesday 13th December 2016

Time: 15.00hrs

Room: L120

Speaker: Rob H. Bisseling (Utrecht University) http://www.staff.science.uu.nl/~bisse101/

Title: Parallel matching for big graphs

Abstract: We present a gentle introduction to the topic of parallelising graph algorithms through the example of an approximation algorithm for matching in big weighted graphs. This algorithm is based on locally dominant edges and partial edge sorting.

We will discuss how to parallelise the algorithm with special attention to load balancing in an irregular setting, tie-breaking between edge weights as a feature, not a bug, and the virtues of 2D (edge) vs. 1D (vertex) partitioning.

We use the Bulk Synchronous Parallel (BSP) model to structure the computation, to analyse the time complexity, and to reason about the correctness of the algorithm.

Date: Tuesday 22nd November 2016

Time: 15.00hrs

Room: L120

Speaker: Fred Wubs (RUG)

Title: HYMLS: A robust multilevel solver for 3D steady flow problems

Abstract: Pseudo-arclength continuation is a powerful technique for investigating parameter sensitivity of complex dynamical systems. However, for three-dimensional fluid dynamics problems the application of this technique is difficult because of the ill-conditioned Jacobian matrices that arise during the process. The indefiniteness of the matrices and the computational complexity makes direct solvers inefficient in 3D, while iterative solvers typically lack robustness at high Reynolds numbers. In the talk we first will discuss general direct and iterative approaches to solve linear systems. Next we will indicate the special properties of the system of equations arising from the finite volume discretization of the incompressible Navier-Stokes equations and the difficulties this gives in solving them. Finally, we present the hybrid direct/iterative solver HYMLS for the Jacobian of the incompressible Navier-Stokes equations on structured grids. Among others, we will show results of computations on a 3D lid driven cavity near the first Hopf bifurcation.

Date: Tuesday 1st November 2016

Time: 15.00hrs

Room: L120

Speaker: Richard Dwight (TU Delft)

Title: Data-mining for the design and analysis of turbulence closure models

Abstract: An introduction and overview of recent work in estimating model inadequacy (the error in simulation resulting from modelling assumptions) in Reynolds-averaged Navier-Stokes. The modelling problem is introduced, and the key modelling assumptions are analysed. The objective is to quantify the resulting error in the solution - and several approaches have been proposed, all founded on principles of uncertainty quantification. These will be discussed, and directions for future work considered.

Date: Tuesday 18th October 2016

Time: 15.00hrs

Room: L120

Speaker: Anna Dubinova (Scientific Computing, CWI)

Title: Modeling of streamer discharges near dielectrics

Abstract: Streamers developing near dielectrics or on dielectric surfaces are usually to be avoided in high voltage technology, because they are often precursors to sparks and dielectric breakdown. My PhD research was part of the "Creeping Sparks" project, which was initiated to better understand surface flashovers and thus to contribute to the development of more efficient and reliable high voltage infrastructures.

I will tell about the progress that was made in understanding streamer discharge behavior near dielectrics and about the dedicated numerical tools that I developed in the course of my PhD research. Among them are a Poisson solver with the Ghost Fluid Method incorporated in it and an alternative approach to calculation of integrals for photoionization and photoemission.

I will also tell about another application of my streamer discharge model. Essentially, the problem of streamer development near dielectrics is also relevant in the context of lightning inception in thunderclouds, and with my colleagues we proposed the first self-consistent model of lightning inception.

Date: Tuesday 27 September 2016

Time: 15.00hrs

Room: L120

Speaker: Luis Ortiz Gracia (Department of Econometrics, Statistics and Applied Economics, University of Barcelona, Barcelona, Spain)

Title: A dimension reduction method for option pricing (in collaboration with Duy-Minh Dang)

Abstract: We present a robust and highly efficient Shannon-wavelet based dimension reduction method for computing plain-vanilla European option prices under general jump-diffusion models with stochastic variance and multi-factor Gaussian interest rates. Using the conditional Monte Carlo technique applied to the variance factor, the option price can be expressed as a two-level nested conditional expectation. The inner expectation is then evaluated analytically, with the variances associated with all the interest rates factors completely removed from the analytical solution. The outer expectation is approximated very efficiently by means of the Shannon Wavelets Inverse Fourier Technique (SWIFT) via evaluating a single integral that involves only the variance factor. Central to this process is a highly effcient recovery of the conditional density of the time-integrated variance process using the SWIFT method. Furthermore, the SWIFT method also allows us to develop sharp approximation error bounds for the option price. Numerical experiments confirm the robustness and efficiency of the proposed pricing method.

*[1] Dang D.M., Ortiz-Gracia, L. A dimension reduction Shannon-wavelet based method for option pricing. Submitted for publication, 2016. ** [2] Ortiz-Gracia L., Oosterlee, C.W. A highly efficient Shannon wavelet inverse Fourier technique for pricing European options. SIAM Journal on Scientific Computing, 38(1), B118-B143, 2016.*

Date: Friday 9 September 2016

Time: 14.00hrs (different day and time!)

Room: L120

Speaker: Wim Vanroose, Department of Mathematics and Computer Science, U. Antwerpen. Belgium (guest of Menno Genseberger)

Title: Elimination of communication bottlenecks from Krylov Methods

Abstract: Modern HPC machines have three levels of parallelism: 1) Many CPUs 2) each CPU has multiple cores and 3) each core has SIMD instructions that work with long vectors. To handle this dramatic increase of parallelism communication and synchronisation is of increasing importance. Long latencies and limited memory bandwidth can lead to stalling performance. In this talk we discuss efforts to redesign Krylov subspace methods that avoid communication and hide latencies. These methods give a better scalability to a large number of CPUs.

Date: Tuesday 6 September 2016

Time: 15.00hrs

Room: L120

Speaker: Benjamin Sanderse (Scientific Computing, CWI)

Title: Energy, fluid flow, and numerical mathematics: from applications to differential equations

Abstract: What is the relation between flow of oil and gas in pipelines and index-3 differential-algebraic equations? How can shock waves appear in Darcy-type problems in reservoirs? And how can model averaging lead to ill-posed differential equations? These and other questions will be addressed in my talk, in which I will give an overview of my work on solving fluid flow problems for several problems in the energy industry: wind turbine wakes in wind farms, transport of oil and gas in pipelines, and multi-phase flow in subsurface reservoirs.

Date: Tuesday 14 June 2016

Time: 15.00hrs

Room: L120

Speaker: Dirk Roose (KU Leuven)

Title: Multi-scale simulation of forming processes with polycrystalline materials

Date: Tuesday 24 May 2016

Time: 15.00hrs

Room: L120

Speaker: Chris Stolk (UvA)

Title: Recent results on the discretization and solution of time harmonic wave equations

Abstract: Time-harmonic wave equations, acoustic or electromagnetic, have many applications, e.g. in seismology and scattering theory. In this talk we consider the Helmholtz equation for time-harmonic acoustic waves in the high-frequency limit, i.e. in the case of waves propagating over long distances. We present a new finite difference discretization, based on Fourier analysis and geometrical optics. It yields accurate simulation results using very few grid points per wave length, in case the medium varies smoothly. By using it within a multigrid method, possibly combined with domain decomposition, more general Helmholtz problems can be efficiently solved.

Date Tuesday 3 May 2016

Time: 15.00hrs

Room: L120

Speaker: Martina Chirilus-Bruckner (Leiden University)

Title: Dynamics and inverse spectral theory

Abstract: This talk will illustrate along the example of a nonlinear wave equation with periodic coefficients, how a classical dynamical systems technique such as center manifold reduction can be extended to settings that, at first sight, seem out of reach by solving an inverse spectral problem. This is joint work with C.E. Wayne.

Date Tuesday 26 April 2016

Different time: 14.00(!)-15.00

Room: L120

Speaker: Valerio Lucarini (Universität Hamburg, Meteorological Institute / University of Reading, UK)

Title: Response and Fluctuations in Geophysical Fluid Dynamics

Abstract: The climate is a complex, chaotic, non-equilibrium system featuring a limited horizon of predictability, variability on a vast range of temporal and spatial scales, instabilities resulting into energy transformations, and mixing and dissipative processes resulting into entropy production. Despite great progresses, we still do not have a complete theory of climate dynamics able to encompass instabilities, equilibration processes, and response to changing parameters of the system. We will outline some possible applications of the response theory developed by Ruelle for non-equilibrium statistical mechanical systems, showing how it allows for setting on firm ground and on a coherent framework concepts like climate sensitivity, climate response, and climate tipping points. We will show results for comprehensive global climate models. The results are promising in terms of suggesting new ways for approaching the problem of climate change prediction and for using more efficiently the enormous amounts of data produced by modeling groups around the world.

*V. Lucarini, R. Blender, C. Herbert, F. Ragone, S. Pascale, J. Wouters, Mathematical and Physical Ideas for Climate Science, Reviews of Geophysics 52, 809-859 (2014).*

Date: Tuesday 12 April 2016

Time: 15.00hrs

Room: L120

Speaker: Sonja Cox (UvA)

Title: numerical approximation of stochastic partial differential equations

Abstract: In my talk I will give an overview of numerical analysis for stochastic partial differential equations. In particular, I will explain the different types of convergence one may consider, the rates of convergence one may expect, and explain under what conditions convergence has been proven. In particular, I will explain a little about my own work on weak convergence for semi-linear SPDEs.

Date: Tuesday 22 March 2016

Time: 15.00hrs

Room: L120

Speaker: Sander van Oers (NIOZ)

Title: Hamiltonian discontinuous Galerkin FEM for linear, stratified (in)compressible Euler equations: internal gravity waves

Abstract: The linear equations governing internal gravity waves in a stratified ideal fluid possess a Hamiltonian structure. A discontinuous Galerkin finite element method has been developed in which this Hamiltonian structure is discretized, resulting in conservation of discrete analogs of phase space and energy. This required (1) the discretization of the Hamiltonian structure using alternating flux functions and symplectic time integration, (2) the discretization of a divergence-free velocity field using Dirac's theory of constraints and (3) the handling of the large-scale computational demands due to the three-dimensional nature of internal gravity waves and, in confined, symmetry-breaking fluid domains, possibly its narrow zones of attraction.

Date: Tuesday 8 March 2016

Time: 15.00hrs

Room: L120

Speaker: Jannis Teunissen (Multiscale Dynamics, CWI)

Title: Developing 3D simulation models for electric discharges

Abstract: An electric discharge occurs when electric charge suddenly starts to flow through an insulator such as air. Examples of discharges are lightning, fluorescent lamps, and the small sparks that sometimes occur when taking of a sweater. After a brief introduction of the underlying mechanisms, my talk will focus on numerical models for discharges.

Discharges are often true multiscale phenomena, which makes adaptive mesh refinement combined with a very fast Poisson solver a necessity for 3D simulations. To fulfill these requirements, I have developed a small framework for finite volume simulations on quadtree/octree grids, which includes a geometric multigrid solver. I will demonstrate current possibilities, and conclude with an outlook on future improvements.

Date: Tuesday 23 February 2016

Time: 15.00hrs

Room: L120

Speaker: Dr. Sigrun Ortleb, University of Kassel, homepage (guest of Willem Hundsdorfer)

Title: On Patankar-type time integration preserving non-negative water height within a discontinuous Galerkin shallow water code

Abstract: Discontinuous Galerkin(DG) methods are a modern and popular class of numerical methods especially for computationally intensive fluid dynamics calculations. Their popularity is due to the fact that DG methods allow for high order approximations in combination with high flexibility – e.g. in choosing different polynomial degrees on neighbouring elements. In this talk, we consider the application of the DG scheme on unstructured triangular grids to hyperbolic conservation laws. Briefly, we will show their connection to summation-by-parts(SBP) operators which posess very convenient stability properties.

We then focus on the application of the DG scheme to shallow water flows with non-flat bottom topography. In particular, the DG scheme then has to guarantee non-negativity of the water height. For locally refined grids at wet/dry interfaces, the stability and positivity requirements of explicit time integration unfortunately lead to rather restrictive time step constraints. However, the non-negativity requirement usually restricts the time step in the implicit case as well. In this context, we consider modified Patankar-type time integration methods which preserve non-negativity of the water height for any time step size.

Date: Tuesday 2 February 2016

Time: 15.00hrs

Room: L120

Speaker: Wim Verkley (Royal Netherlands Meteorological Institute (KNMI), R&D Weather and Climate Models)

Title: Parameterization of unresolved processes - can the principle of maximum entropy help us out?

Abstract: No matter how high the resolution of weather and climate models becomes, the need to represent all processes that are not resolved explicitly will stay with us in the foreseeable future. This is illustrated rather dramatically by the fact that in the atmosphere the ultimate sink of the kinetic energy of moving air is at spatial scales of the order of a millimeter. And there are many other processes whose intricacy makes it impossible to model these explicitly and deterministically. To take the unresolved processes into account, parameterizations have been devised such as the eddy viscosity proposed by Boussinesq or the eddy parameterizaton introduced by Smagorinsky his 1963 paper on one of the first general circulation models of the atmosphere. Although these and other parameterization schemes work reasonably well, there is a large heuristic element in their design and a corresponding need to tune their parameters. One particular problem is that they do not adjust themselves automatically to a change in model resolution. By representing the unresolved processes by a probability density function and determining its explicit form by applying the principle of maximum entropy, it is possible to derive parameterization schemes in a rather systematic way. The resulting schemes have some interesting properties such as the absence of tunable parameters. A simple two-dimensional fluid system will be used to illustrate how this works in practice.

Date: Tuesday 8 December 2015

Time: 15.00hrs

Room: L120

Speaker: Willem Hundsdorfer (Multiscale Dynamics, CWI)

Title: Multirate methods for conservation laws

Abstract: In this talk we will discuss explicit multirate one-step schemes for conservation laws and convection-dominated problems. Different regions of the spatial PDE domain may then have different (local) time steps. Such schemes can be conveniently represented as partitioned Runge-Kutta methods. It is known that standard Runge-Kutta methods may suffer from order reduction when used as time stepping scheme for a PDE with boundary conditions. For multirate schemes, the interfaces act as time-dependent boundary conditions. This may lead to a very disappointing accuracy. Theoretical results will be presented on the order of accuracy of some interesting multirate schemes, with cell-based and flux-based decompositions, together with numerical illustrations.

Date: Tuesday 24 November 2015

Time: 15.00hrs

Room: L120

Speaker: Laurent van den Bos (Scientific Computing, CWI)

Title: Fast Non-Intrusive Uncertainty Quantification, with Applications to Fluid Flows

Abstract: here.

Date: Thursday 5 November 2015

Time: 15.00hrs

Room: L120

Speaker: Prof. Carsten Carstensen (Humboldt-Universität zu Berlin, Germany)

Title: Axioms of Adaptivity: Rate optimality of adaptive algorithms with separate marking

Abstract: here.

Date: 3 July 2015

Time: 11.30hrs

Room: L120

Speaker: A/Prof Frances Kuo (School of Mathematics and Statistics, University of New South Wales, Sydney NSW Australia)

Title: Multi-Level Quasi-Monte Carlo Methods for PDEs with random coefficients

Abstract: High dimensional problems are coming to play an ever more important role in applications, including, for example, option pricing problems in mathematical finance, maximum likelihood problems in statistics, and porous flow problems in computational physics and uncertainty quantification. High dimensional problems pose immense challenges for practical computation, because of a nearly inevitable tendency for the cost of computation to increase exponentially with dimension. Effective and efficient methods that do not suffer from this "curse of dimensionality" are in great demand, especially since some practical problems are in fact infinite dimensional.

In this talk I will start with an introduction to "quasi-Monte Carlo methods", focusing on the theory and construction of "lattice rules" (order one) and "interlaced polynomial lattice rules" (higher order) developed in the past decade. Then I will showcase our very latest work on how this modern theory can be "tuned" for a given application. The motivating example will involve an elliptic PDE with a random coefficient, which is based on a simplified porous flow problem where the permeability is modeled as a random field.

Date: 2 February 2015

Time: 14.30hrs

Room: L120

Speaker: Mario Annunziato (Università degli Studi di Salerno (www.dipmat.unisa.it/people/annunziato/www/) )

Title: Fokker-Planck optimal control of anomalous diffusion processes

Abstract: We deal with the optimal control of stochastic processes related to the anomalous diffusion. To achieve this aim we use the Model Predictive Control technique associated to a new framework based on the fractional Fokker-Planck equation. It is based on the probability density function (PDF) as representative of the state of the stochastic system and it is formulated as the problem of minimizing a cost function in terms of the PDF. The problem to find the controller that minimize the cost function is solved by solving an optimality system of fractional forward and backward partial differential equations. We illustrate the numerical scheme and the results of the related experiments. Finally, the extension of this technique to the control of piecewise deterministic process is outlined.

Date: 12 January 2015

Time: 10.30 - 11.30hrs

Room: L120

Speaker: Halldora Thorsdottir (Life Sciences, CWI)

Title: Infinite servers in a random environment

Abstract: Queueing theory provides a simple framework to model discrete, stochastic systems, with applications ranging from telecommunications to chemical reaction networks. For many cases, it offers exact analytical expressions for moments and distributions of classical performance measures, such as number-in-system and time-in-system. By embedding an infinite server queueing system in a random environment, we allow for a Markovian variation of the main parameters which makes the model more realistic and complex to analyze, preventing us from finding exact expressions. Simultaneous, but unequal, scaling of the two-layered system exaggerates its two time-scales and leads to approximations for the distributions of the quantities of interest. Here the right balance in the scaling is required, and will determine the variance of the resulting process. We see at which level the main system behaves almost independently of the environmentand vice versa. The result is a central limit theorem, with techniques including generating functions and ODEs.

Speaker: Jeroen Witteveen (Scientific Computing, CWI)

Title: Quantifying Errors and Uncertainties in Wind Engineering

Abstract: Predictions of computer simulation codes need to be validated in comparisons with experimental measurements. However, these observations also contain errors and uncertainties, usually reported as experimental confidence bars. The errors and uncertainties in the numerical results therefore have to be quantified as well to enable a rigorous comparison. Important examples of these are numerical discretization error, model form uncertainty, and uncertainty in model input parameter values. The Benchmark on the Aerodynamics of a Rectangular Cylinder (BARC) is an interesting example in this respect. It is a test case from the field of wind engineering for the flow of wind around buildings and bridges. A large number of computer simulations and wind tunnel experiments have been performed by different research groups for this challenging benchmark. However, none of these numerical studies have quantified the uncertainties in a robust probabilistic way so far. We are quantifying the impact of the spatial discretization error, the turbulence model uncertainty, and the probabilistic input parameter uncertainty in this case for the first time. The challenge is to develop methods that can rigorously combine these different sources of uncertainty and error. The results will be compared to the extensive BARC database. This is collaborative work with TNO and the University of Pisa.