[current research topic]
I am an industrial research fellow at the Computer Laboratory.
My PhD [contents 1 2 3 figs 4 ] was in theoretical and experimental superconductivity at the Cavendish Laboratory in Cambridge. I did a postdoc at the National Bureau of Standards in Boulder, Colorado and became a fellow of Trinity College, Cambridge.
By calculating how the phase of the superconducting order parameter [defined in Brian Josephson's thesis] transforms as the superconductor accelerates and rotates, I established a quantitative relationship with the electromagnetic field [pdf] and a correction to the London moment of a rotating superconductor [pdf], which was a candidate at the time for measuring the ratio of charge to mass of the electron. I predicted a new effect which could be used to make a superconducting gyroscope with no moving parts, published here. Subsequently Jim Zimmerman and I measured it experimentally [pdf and figures]. In principle the effect could be used to measure gravitational fields and waves [pdf] but the sources of noise are likely to make the apparatus impracticable.
It turns out that the mass of copper within radius r of a point cathode is proportional to rD. We could measure D because the mass of copper is proportional to the total charge transferred, and the radius is proportional to the current. The experimental result was D = 2.43 ± 0.03, in agreement with previous simulation work.
Subsequently I wrote a computer progaram to model this behaviour. This briefly held the record for the largest simulations (we were using a timeshare on an IBM and our competitors were using a supercomputer -- we lost this crown when my algorithm was adopted on these computers). The program was used in papers together with Robin Ball, Giuseppe Rossi and Bernard Thompson [1 2 3 4].
Such algorithms do not perform very well. For example, if the computer has found a good route round England but a poor route around Scotland, it must temporarily make the English route longer in order to improve the Scottish route - a problem which it is computationally expensive to overcome.
Biological evolution encounters the same problem. But if you can out-evolve your competitors, you will win in the long run. There have been billions of years to solve this problem - and the answer is sex. Learning from this, I created multiple solutions to the travelling salesman problem, and performing a 'cross-over'. In the above example, a solutions with a good route round England would be crossed with others, some of which would have a good route round Scotland. I beat the then-fastest algorithms for the travelling salesman problem. The paper was published in Nature.
Together with Ross Anderson and Robin Ball, I demonstrated that computer programmers face the worst of all possible worlds when it comes to bugs: Murphy's law, the fitness of evolving species, and the limits of software reliability.
There is a separate page on this topic with links to animations and presentations.
I mentor technology startups and am the treasurer of the Cambridge Angels. I am a director of Cambridge Intellectual Property Ltd, which analyses patents, and I am chairman of Undo Software Ltd, which supplies reverse debugging tools that allow you to execute a program backwards until you reach a breakpoint.
I play the game of real tennis (which is the game they played before they invented lawn tennis) with a handicap of 63.
By default, when I post a paper here I license it under the relevant Creative Commons license, so you may redistribute it with attribution but not modify it. I may subsequently assign the residual copyright to an academic publisher.
University of Cambridge
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