L3

Most sensing systems exhibit so-called ‘sidelobe’ responses, which can be interpreted as an inevitable effect in one domain of truncation of the signal in the Fourier-complement domain.  Perhaps the best-known example is in antenna theory where sidelobes are an inevitable consequence of the fact that the antenna aperture must be finite.  The effect also appears in many other places, for example in time-frequency conversions and in the range domain of a pulse-compressed radar which radiates a signal only over a finite frequency band.  In the range domain these sidelobes extend over twice the length of the transmitted pulse.  For a conventional radar with relatively short pulses the effect of these unwanted returns is thus confined to a relatively short part of the range swathe.

Some of the most modern radar techniques, however, use continuous, noise-like transmissions.  ‘Primary’ noise-modulated radars are in their infancy but so-called ‘Passive’ radars using broadcast transmissions as their power source receive similar signals.  The sidelobes of even a small target at very short range can be larger than the main return from a target at much greater range.  This limits the dynamic range of the radar.

Since, however, the sidelobe pattern is predictable if the illuminating signal is known sufficiently accurately, the expected sidelobes due to a large target can be estimated and removed to tidy up the image.  This approach was first described formally in:

Hoegbom, J. A., ‘Aperture Synthesis with a Non-Regular Distribution of Interferometer Baselines,’ Astrom. Astrophys. Suppl. 15, pp417-26, 1974.

And is generally known by the name of the ‘CLEAN’ algorithm.

The seminar will outline the problem, outline the basic form of the algorithm and ask questions about what is possible with non-iterative versions of the algorithms, how to process the data coherently and how to understand any stability issues associated with the algorithm.

Abstract: Motivated loosely by the problem of carbon sequestration in underground aquifers, I will describe computations and analysis of one-sided two-dimensional convection of a solute in a fluid-saturated porous medium, focusing on the case in which the solute decays via a chemical reaction.   Scaling properties of the flow at high Rayleigh number are established and rationalized through an asymptotic model, that addresses the transient stability of a near-surface boundary layer and the structure of slender plumes that form beneath.  The boundary layer is shown to restrict the rate of solute transport to deep domains.  Knowledge of the plume structure enables slow erosion of the substrate of the reaction to be described in terms of a simplified free boundary problem.

Co-authors: KA Cliffe, H Power, DS Riley, TJ Ward

1. A Hybrid Monte-Carlo Partial Differential Solver for Stochastic  Volatility Models (Cozma)

In finance, Monte-Carlo and Finite Difference methods are the most popular approaches for pricing options. If the underlying asset is modeled by a multidimensional system of stochastic differential equations, an analytic solution is rarely available and working under a given computational budget comes at the cost of accuracy. The mixed Monte-Carlo partial differential solver introduced by Loeper and Pironneau (2009) is one way to overcome this issue and we investigate it thoroughly for a number of stochastic volatility models. Our main concern is to provide a rigorous mathematical proof of the convergence of the hybrid method under different frameworks, which in turn justifies the use of Monte-Carlo simulations to compute the expected discounted payoff of the financial derivative. Then, we carry out a quantitative assessment based on a European call option by comparison with alternative numerical methods.

2. tbc (Brackmann)

Particle-based stochastic reaction diffusion methods have become a 
popular approach for studying the behavior of cellular processes in 
which both spatial transport and noise in the chemical reaction process 
can be important. While the corresponding deterministic, mean-field 
models given by reaction-diffusion PDEs are well-established, there are 
a plethora of different stochastic models that have been used to study 
biological systems, along with a wide variety of proposed numerical 
solution methods.

In this talk I will motivate our interest in such methods by first 
summarizing several applications we have studied, focusing on how the 
complicated ultrastructure within cells, as reconstructed from X-ray CT 
images, might influence the dynamics of cellular processes. I will then 
introduce our attempt to rectify the major drawback to one of the most 
popular particle-based stochastic reaction-diffusion models, the lattice 
reaction-diffusion master equation (RDME). We propose a modified version 
of the RDME that converges in the continuum limit that the lattice 
spacing approaches zero to an appropriate spatially-continuous model. 
Time-permitting, I will discuss several questions related to calibrating 
parameters in the underlying spatially-continuous model.

The folded structures of proteins display a remarkable variety of three-dimensional forms, and this structural diversity confers to proteins their equally remarkable functional diversity. The accelerating accumulation of experimental structures, and the declining numbers of novel folds among them suggests that a substantial fraction of the protein folds used in nature have already been observed. The physical forces stabilizing the folded structures of proteins are now understood in some detail, and much progress has been made on the classical problem of predicting the structure of a particular protein from its sequence. However, there is as yet no satisfactory theory describing the “morphology” of protein folds themselves. This talk will describe an approach to this problem based on the description of protein folds as geometric objects using the differential geometry of curves and surfaces. Applications of the theory toward modeling of diverse protein folds and assemblies which are refractory to high-resolution structure determination will be emphasized.

Droplet impacts form an important part of many processes and a detailed
understanding of the impact dynamics is critical in determining any
subsequent splashing behaviour. Prior to touchdown a gas squeeze film is
set-up between the substrate and the approaching droplet. The pressure
build-up in this squeeze film deforms the droplet free-surface, trapping
a pocket of gas and delaying touchdown. In this talk I will discuss two
extensions of existing models of pre-impact gas-cushioned droplet
behaviour, to model droplet impacts with textured substrates and droplet
impacts with surfaces hot enough to induce pre-impact phase change.

In the first case the substrate will be modelled as a thin porous layer.
This produces additional pathways for some of the gas to escape and
results in less delayed touchdown compared to a flat plate. In the
second case ideas related to the evaporation of heated thin viscous
films will be used to model the phase change. The vapour produced from
the droplet is added to the gas film enhancing the existing cushioning
mechanism by generating larger trapped gas pockets, which may ultimately
prevent touchdown altogether once the temperature enters the Leidenfrost
regime.