Please note that the list below only shows forthcoming events, which may not include regular events that have not yet been entered for the forthcoming term. Please see the past events page for a list of all seminar series that the department has on offer.
We first consider multilevel Monte Carlo and stochastic collocation methods for determining statistical information about an output of interest that depends on the solution of a PDE with inputs that depend on random parameters. In our context, these methods connect a hierarchy of spatial grids to the amount of sampling done for a given grid, resulting in dramatic acceleration in the convergence of approximations. We then consider multifidelity methods for the same purpose which feature a variety of models that have different fidelities. For example, we could have coarser grid discretizations, reduced-order models, simplified physics, surrogates such as interpolants, and, in principle, even experimental data. No assumptions are made about the fidelity of the models relative to the “truth” model of interest so that unlike multilevel methods, there is no a priori model hierarchy available. However, our approach can still greatly accelerate the convergence of approximations.
- Computational Mathematics and Applications Seminar
We discuss two Freidlin-Wentzell large deviation principles for McKean-Vlasov equations (MV-SDEs) in certain path space topologies. The equations have a drift of polynomial growth and an existence/uniqueness result is provided. We apply the Monte-Carlo methods for evaluating expectations of functionals of solutions to MV-SDE with drifts of super-linear growth. We assume that the MV-SDE is approximated in the standard manner by means of an interacting particle system and propose two importance sampling (IS) techniques to reduce the variance of the resulting Monte Carlo estimator. In the "complete measure change" approach, the IS measure change is applied simultaneously in the coefficients and in the expectation to be evaluated. In the "decoupling" approach we first estimate the law of the solution in a first set of simulations without measure change and then perform a second set of simulations under the importance sampling measure using the approximate solution law computed in the first step.
- Mathematical and Computational Finance Seminar
In laboratories around the world, scientists use magnetic stirrers to mix solutions and dissolve powders. It is well known that at high drive rates the stir bar jumps around erratically with poor mixing, leading to its nick-name 'flea'. Investigating this behaviour, we discovered a state in which the flea levitates stably above the base of the vessel, supported by magnetic repulsion between flea and drive magnet. The vertical motion is oscillatory and the angular motion a superposition of rotation and oscillation. By solving the coupled vertical and angular equations of motion, we characterised the flea’s behaviour in terms of two dimensionless quantities: (i) the normalized drive speed and (ii) the ratio of magnetic to viscous forces. However, Earnshaw’s theorem states that levitation via any arrangement of static magnets is only possible with additional stabilising forces. In our system, we find that these forces arise from the flea’s oscillations which pump fluid radially outwards, and are only present for a narrow range of Reynold's numbers. At slower, creeping flow speeds, only viscous forces are present, whereas at higher speeds, the flow reverses direction and the flea is no longer stable. We also use both the levitating and non-levitating states to measure rheological properties of the system.
- Industrial and Applied Mathematics Seminar
- Industrial and Interdisciplinary Workshops
- Applied Algebra and Topology
- Mathematical Finance Internal Seminar
1600-1645 - Philip Maini
1645-1705 - Edward Morrissey
1705-1725 - Heather Harrington
1725-1800 - Drinks and networking
The talks will be followed by a drinks reception.
Tickets can be obtained from https://www.eventbrite.co.uk/e/qbiox-colloquium-trinity-term-2018-ticket....
(As ever, tickets are not necessary, but they do help in judging catering requirements.)
Does mathematics have anything to do with biology? In this talk, I will review a number of interdisciplinary collaborations in which I have been involved over the years that have coupled mathematical modelling with experimental studies to try to advance our understanding of processes in biology and medicine. Examples will include somatic evolution in tumours, collective cell movement in epithelial sheets, cell invasion in neural crest, and pattern formation in slime mold. These are examples where verbal reasoning models are misleading and insufficient, while mathematical models can enhance our intuition.
Fixation and spread of somatic mutations in adult human colonic epithelium Cancer causing mutations must become permanently fixed within tissues. I will describe how, by visualizing somatic clones, we investigated the means and timing with which this occurs in the human colonic epithelium. Modelling the effects of gene mutation, stem cell dynamics and subsequent lateral expansion revealed that fixation required two sequential steps. First, one of around seven active stem cells residing within each colonic gland has to be mutated. Second, the mutated stem cell has to replace neighbours to populate the entire gland. This process takes many years because stem cell replacement is infrequent (around once every 9 months). Subsequent clonal expansion due to gland fission is also rare for neutral mutations. Pro-oncogenic mutations can subvert both stem cell replacement to accelerate fixation and clonal expansion by gland fission to achieve high mutant allele frequencies with age. The benchmarking and quantification of these behaviours allows the advantage associated with different gene specific mutations to be compared and ranked irrespective of the cellular mechanisms by which they are conferred. The age related mutational burden of advantaged mutations can be predicted on a gene-by-gene basis to identify windows of opportunity to affect fixation and limit spread.
Comparing models with data using computational algebra In this talk I will discuss how computational algebraic geometry and topology can be useful for studying questions arising in systems biology. In particular I will focus on the problem of comparing models and data through the lens of computational algebraic geometry and statistics. I will provide concrete examples of biological signalling systems that are better understood with the developed methods.