Gibson Grd floor SR

The Arnoldi method for standard eigenvalue problems possesses several

attractive properties making it robust, reliable and efficient for

many problems. We will present here a new algorithm equivalent to the

Arnoldi method, but designed for nonlinear eigenvalue problems

corresponding to the problem associated with a matrix depending on a

parameter in a nonlinear but analytic way. As a first result we show

that the reciprocal eigenvalues of an infinite dimensional operator.

We consider the Arnoldi method for this and show that with a

particular choice of starting function and a particular choice of

scalar product, the structure of the operator can be exploited in a

very effective way. The structure of the operator is such that when

the Arnoldi method is started with a constant function, the iterates

will be polynomials. For a large class of NEPs, we show that we can

carry out the infinite dimensional Arnoldi algorithm for the operator

in arithmetic based on standard linear algebra operations on vectors

and matrices of finite size. This is achieved by representing the

polynomials by vector coefficients. The resulting algorithm is by

construction such that it is completely equivalent to the standard

Arnoldi method and also inherits many of its attractive properties,

which are illustrated with examples.

Exponential time integrators are a powerful tool for numerical solution

of time dependent problems. The actions of the matrix functions on vectors,

necessary for exponential integrators, can be efficiently computed by

different elegant numerical techniques, such as Krylov subspaces.

Unfortunately, in some situations the additional work required by

exponential integrators per time step is not paid off because the time step

can not be increased too much due to the accuracy restrictions.

To get around this problem, we propose the so-called time-stepping-free

approach. This approach works for linear ordinary differential equation (ODE)

systems where the time dependent part forms a small-dimensional subspace.

In this case the time dependence can be projected out by block Krylov

methods onto the small, projected ODE system. Thus, there is just one

block Krylov subspace involved and there are no time steps. We refer to

this method as EBK, exponential block Krylov method. The accuracy of EBK

is determined by the Krylov subspace error and the solution accuracy in the

projected ODE system. EBK works for well for linear systems, its extension

to nonlinear problems is an open problem and we discuss possible ways for

such an extension.

We present recent numerical techniques for the treatment of integral formulations of Helmholtz boundary value problems in the case of high frequencies. The combination of $H^2$-matrices with further developments of the adaptive cross approximation allows to solve such problems with logarithmic-linear complexity independent of the frequency. An advantage of this new approach over existing techniques such as fast multipole methods is its stability over the whole range of frequencies, whereas other methods are efficient either for low or high frequencies.

Although much work has been done on using RBFs for reconstructing arbitrary surfaces, using RBFs to solve PDEs on arbitrary manifolds is only now being considered and is the subject of this talk. We will review current methods and introduce a new technique that is loosely inspired by the Closest Point Method. This new technique, the Orthogonal Gradients Method (OGr), benefits from the advantages of using RBFs: the simplicity, the high accuracy but also the meshfree character, which gives the flexibility to represent the most complex geometries in any dimension.

The talk will survey recent developments concerning the existence and the approximation of global weak solutions to a general class of coupled microscopic-macroscopic bead-spring chain models that arise in the kinetic theory of dilute solutions of polymeric liquids with noninteracting polymer chains. The class of models involves the unsteady incompressible Navier-Stokes equations in a bounded domain for the velocity and the pressure of the fluid, with an elastic extra-stress tensor appearing on the right-hand side of the momentum equation. The extra-stress tensor stems from the random movement of the polymer chains and is defined by the Kramers expression through the associated probability density function that satisfies a Fokker-Planck type parabolic equation. Models of this kind were proposed in work of Hans Kramers in the early 1940's, and the existence of global weak solutions to the model has been a long-standing question in the mathematical analysis of kinetic models of dilute polymers.

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We also discuss computational challenges associated with the numerical approximation of the high-dimensional Fokker-Planck equation featuring in the model.

The periodic orbits of a discrete dynamical system can be described as

permutations. We derive the composition law for such permutations. When

the composition law is given in matrix form the composition of

different periodic orbits becomes remarkably simple. Composition of

orbits in bifurcation diagrams and decomposition law of composed orbits

follow directly from that matrix representation.

Please email @email to enquire about attending this meeting

Biomedical science relies on the parallel development of mathematical and experimental models to progress understanding and develop new approaches to the diagnosis, treatment and monitoring of disease. Recognition is growing that knowledge of the roles of physical and mechanical processes in influencing and controlling biological responses in living systems is critical in order for the great promise of tissue engineering and regenerative therapies to be fulfilled. This field of study of physical and mechanical effects on biology is known as mechanobiology, and requires close collaboration between clinicians, biologists, mathematicians and engineers to advance. The aim of this meeting is to bring together researchers in biomedical engineering, biology, and mathematical biology to discuss the latest developments in this fast moving field, the close collaboration across disciplines ensuring that mathematical and biological models develop in parallel, so plenty of time will be allotted for discussion and for more informal interaction.

https://www.maths.ox.ac.uk/groups/occam/events/occam-hosts-mathematical-and-experimental-models-mechanobiology-conference

In this talk I review the use of the spectral decomposition for understanding the solution of ill-posed inverse problems. It is immediate to see that regularization is needed in order to find stable solutions. These solutions, however, do not typically allow reconstruction of signal features such as edges. Generalized regularization assists but is still insufficient and methods of total variation are commonly suggested as an alternative. In the talk I consider application of standard approaches from Tikhonov regularization for finding appropriate regularization parameters in the total variation augmented Lagrangian implementations. Areas for future research will be considered.

In this talk we present an overview of some recent developments concerning the a posteriori error analysis and adaptive mesh design of $h$- and $hp$-version discontinuous Galerkin finite element methods for the numerical approximation of second-order quasilinear elliptic boundary value problems. In particular, we consider the derivation of computable bounds on the error measured in terms of an appropriate (mesh-dependent) energy norm in the case when a two-grid approximation is employed. In this setting, the fully nonlinear problem is first computed on a coarse finite element space $V_{H,P}$. The resulting 'coarse' numerical solution is then exploited to provide the necessary data needed to linearise the underlying discretization on the finer space $V_{h,p}$; thereby, only a linear system of equations is solved on the richer space $V_{h,p}$. Here, an adaptive $hp$-refinement algorithm is proposed which automatically selects the local mesh size and local polynomial degrees on both the coarse and fine spaces $V_{H,P}$ and $V_{h,p}$, respectively. Numerical experiments confirming the reliability and efficiency of the proposed mesh refinement algorithm are presented.