Condensed concepts

Ben Powell and I have just advertised for a new postdoc position to work with us at the University of Queensland on strongly correlated electron systems. The full ad is here  and people should apply before January 28 through that link.

The Institute of Advanced Study at Durham University has organised a public lecture series, "The Future of the University." The motivation is worthy. In the face of this rapidly changing landscape, urging instant adaptive response, it is too easy to discount fundamental questions. What is the university now for? What is it, what can it be, what should it be? Are the visions of Humboldt and Newman still valid? If so, how? The poster is a bit bizarre. How should it be interpreted? Sadly, it is hard for me to even imagine such a public event happening in Australia. Last week one of the lectures was given by Peter Coveney ,  a theoretical chemist at University College London, on funding for science. His abstract is a bit of rant with some choice words. Funding of research in U.K. universities has been changed beyond recognition by the introduction of the so-called "full economic cost model". The net result of this has been the halving of the number of grant

Today I am giving a cake meeting talk about something a bit different. Over the past year or so I have tried to learn something about "complexity theory", including networks. Here is some of what I have learnt and found interesting. The most useful (i.e. accessible) article I found was a 2008 Physics Today article, The physics of networks by Mark Newman . The degree of a node , denoted k, is equal to the number of edges connected to that node. A useful quantity to describe real-world networks is the probability distribution P(k); i.e. if you pick a random node it gives the probability that the node has degree k. Analysis of data from a wide range of networks, from the internet to protein interaction networks, finds that this distribution has a power-law form, This holds over almost four orders of magnitude. This is known as a scale-free network , and the exponent is typically between 2 and 3. This power law is significant for several reasons. First, it is in

One of the biggest problems in theoretical physics is to explain why the cosmological constant has the value that it does. There are two aspects to the problem. The first problem is that the value is so small, 120 orders of magnitude smaller than what one estimates based on the quantum vacuum energy! The second problem is that the value seems to be finely tuned (to 120 significant figures!) to the value of the mass energy. The problems and proposed (unsuccessful) solutions are nicely reviewed in an article written in 2000 by Steven Weinberg. There seem to be four distinct responses to this problem. 1. Traditional scientific optimism. A yet to be discovered theory will explain all this. 2. Fatalism.  That is just the way things are. We will never understand it. 3. Teleology and Design. God made it this way. 4. The Multiverse . This finely tuned value is just an accident. Our universe is one of zillions possible. Each has different fundamental constants. It is is ama

Superconductivity is arguably the most intriguing example of emergent phenomena in condensed matter physics. The introduction to an endless stream of papers and grant applications mention this. But, so what? Why does this matter? Are we just invoking a "buzzword" or does looking at superconductivity in this way actually help our understanding? When we talk about emergence I think there are three intertwined aspects to consider: phenomena, concepts, and effective Hamiltonians. For example, for a superconductor, the emergent phenomena include zero electrical resistance, the Meissner effect, and the Josephson effect. In a type-II superconductor in an external magnetic field, there are also vortices and quantisation of the magnetic flux through each vortex. The main concept associated with the superconductivity is the spontaneously broken symmetry.  This is described by an order parameter. The figure below shows the different hierarchies of scale associated