Abstract: Joint work with Oleg Zaboronsky (Warwick).

Some one dimensional nearest neighbour particle systems are examples of Pfaffian point processes - where all intensities are determined by a single kernel.In some cases these kernels have appeared in the random matrix literature (where the points are the positions of eigenvalues). We are attempting to use random matrix tools on the particle sytems, and particle tools on the random matrices.

Abstract:   Consider the square $[0,n]^2$ with points from a Poisson point process of intensity 1 distributed within it. In a seminal work, Baik, Deift and Johansson proved that the number of points $L_n$ (length) on a maximal increasing path (an increasing path that contains the most number of points), when properly centered and scaled, converges to the Tracy-Widom distribution. Later Johansson showed that all maximal paths lie within the strip of width $n^{\frac{2}{3} +\epsilon}$ around the diagonal with probability tending to 1 as $n \to \infty$. We shall discuss recent work on the Gaussian behaviour of the length $L_n^{(\gamma)}$ of a maximal increasing path restricted to lie within a strip of width $n^{\gamma}, \gamma< \frac{2}{3}$.

 

TBC

We consider a controlled system, in which an input $X: [0, T] \rightarrow E:= \mathbb{R}^{d}$ is a continuous but potentially highly oscillatory path and the corresponding output $Y$ is the line integral along $X$, for some unknown function $f: E \rightarrow E$. The rough paths theory provides a general framework to answer the question on which mild condition of $X$ and $f$, the integral $I(X)$ is well defined. It is robust enough to allow to treat stochastic integrals in a deterministic way. In this paper we are interested in identification of controlled systems of this type. The difficulty comes from the high dimensionality caused by the input of a function type. We propose novel adaptive and non-parametric algorithms to learn the functional relationship between the  input and the output from the data by carefully choosing the feature set of paths based on the rough paths theory and applying linear regression techniques. The algorithms is demonstrated on a financial application where the task is to predict the P$\&$L of the unknown trading strategy.

Blenders and food processors have been around for years.  However, detailed understanding of the fluid and particle dynamics going on with in the multi-phase flow of the processing chamber as well as the influence of variables such as the vessel geometry, blade geometry, speeds, surface properties etc., are not well understood.  SharkNinja would like Oxford Universities help in developing a model that can be used to gain insight into fluid dynamics within the food processing chamber with the goal being to develop a system that will produce better food processing performance as well as predict loading on food processing elements to enable data driven product design.

Many vacuum cleaners sold claim “no loss of suction” which is defined as having only a very small reduction in peak air power output over the life of the unit under normal operating conditions.  This is commonly achieved by having a high efficiency cyclonic separator combined with a filter which the user washes at regular intervals (typically every 3 months).  It has been observed that some vacuum cleaners show an increase in peak air watts output after a small amount of dust is deposited on the filter.  This effect is beneficial since it prolongs the time between filter washing.  SharkNinja are currently working on validating their theory as to why this occurs.  SharkNinja would like Oxford University’s help in developing a model that can be used to better understand this effect and provide insight towards optimizing future designs.

Although a very simple system from a construction standpoint, creating a drip coffee maker that can be produce a range of coffee sizes from a single cup to a multi-cup carafe presents unique problems.  Challenges within this system result from varying pressure heads on the inlet side, accurate measurement of relatively low flow rates, fluid motive force generated by boilers, and head above the boiler on the outlet side.  Getting all of these parameters right to deliver the proper strength, proper temp, and proper volume of coffee requires in depth understanding of the fluid dynamics involved in the system.  An ideal outcome from this work would be an adaptive model that enables a fluid system model to be created from building blocks.  This system model would include component models for tubing, boilers, flow meters, filters, pumps, check valves, and the like.

It has been conjectured that marine ice sheets (those that

flow into the ocean) are unconditionally unstable when the underlying

bed-slope runs uphill in the direction of flow, as is typical in many

regions underneath the West Antarctic Ice Sheet. This conjecture is

supported by theoretical studies that assume a two-dimensional flow

idealization. However, if the floating section (the ice shelf) is

subject to three-dimensional stresses from the edges of the embayments

into which they flow, as is typical of many ice shelves in Antarctica,

then the ice shelf creates a buttress that supports the ice sheet.

This allows the ice sheet to remain stable under conditions that may

otherwise result in collapse of the ice sheet. This talk presents new

theoretical and experimental results relating to the effects of

three-dimensional stresses on the flow and structure of ice shelves,

and their potential to stabilize marine ice sheets.

There is wide interest in the oceanographic and engineering communities as to whether linear models are satisfactory for describing the largest and steepest waves in open ocean. This talk will give some background on the topic before describing some recent modelling. This concludes that non-linear physics produces only small increases in amplitude over that expected in a linear model — however, there are significant changes to the shape and structure of extreme wave-group caused by the non-linear physics.

Across much of the ablation region of the western Greenland Ice Sheet, hydro-fracture events related to supraglacial lake drainages rapidly deliver large volumes of meltwater to the bed of the ice sheet. We investigate what triggers the rapid drainage of a large supraglacial lake using a Network Inversion Filter (NIF) to invert a dense local network of GPS observations over three summers (2011-2013). The NIF is used to determine the spatiotemporal variability in ice sheet behavior (1) prior to lake drainage, and in response to (2) vertical hydro-fracture crack propagation and closure, (3) the opening of a horizontal cavity at the ice-sheet bed that accommodates the rapid injection of melt-water, and (4) extra basal slip due to enhanced lubrication. We find that the opening and propagation of each summer’s lake-draining hydro-fracture is preceded by a local stress perturbation associated with ice sheet uplift and enhanced slip above pre-drainage background velocities. We hypothesize that these precursors are associated with the introduction of meltwater to the bed through neighboring moulin systems.