RI Christmas Lectures

I’ve been watching the Royal Institution Christmas lectures on FIVE, with Professor Chris Bishop: Hi-tech Trek – The Quest for the Ultimate Computer. The lectures are fun, and especially great for kids. Unfortunately, they seem to have been scheduled at the worst possible time. The lectures are broadcast from 7:15pm-8:00pm. Whilst this may be a prime-time slot, it is unfortunately competing with two major soap operas. I wonder what most people will choose to watch….

I much preferred the old scheduling: These lectures used to be aired over the holiday period (25th-29th) at around noontime. As such, families tended to be sitting around, doing jigsaw puzzles, with the only competing TV being some old film or other. I think this worked. People need a bit of gentle encouragement to engage with science programmes. Pitching them against Coronation Street, alas, will not work.

The 2008 Christmas lectures aren’t available online yet (not sure they should be anyway!), so here’s some Carl Sagan from the 1977 batch for your delectation:

or if you prefer, some Richard Dawkins from 1991:

More books…

kaku21Sometimes I think this blog seems to be turning into a book review site! Hey, I read fast… Well I’ve just finished Parallel worlds by Michio Kaku. Kaku explores many different ideas, all tied together under a general cosmology theme.

The book begins by introducing some of the key concepts of spacetime, the big bang, and the development of some of the main ideas in cosmology. It discusses the growing field of experimental cosmology, using gravitational wave detectors, WMAP satellite data, data from other telescopes (Arecibo, Chandra, VLBA) and projects such as the Sloan Sky Survey, which can give us information about the distribution and density of black holes in the visible universe. A lot of information can be gathered indirectly, for example by analysing gravitational lensing around large objects. This information may be able to reveal some clues as to how close we are to a theory of everything with our current generation of string theories, supersymmetry, and M-theory. As an experimentalist I did appreciate this ‘down to earth’ spin in addition to the usual speculation of this type of book.

I find it rather impressive that we are able to answer (or at least ask) questions about physics beyond the largest scales with which we currently are familiar (the size of our universe) and the smallest (the planck length scale) using the same theories and data. I’ve always had a passing interest in string theory. I would however get something a little more mathematical next time, this was very easy reading. I was actually dying to see some equations by the end of it, I think it would have enhanced the book and grounded it a little more. (I’ve got Peter Woit’s Not Even Wrong waiting on my shelf to be read at some point, that will probably satisfy my urge for something heavier!)

My other criticism of the book is that it tended to repeat itself a bit in places, especially the more esoteric sections about baby universes and potential escape of civilisation from an accelerating, dying universe. The sections on string theory were also a little confusing in places, mostly because the development of modern string theories was reported ‘chronologically’. This meant that the book kept changing the number of dimensions in the theories, to explain how and why they were ‘in fashion’ at the time. I’d rather have just heard about the latest ones here, the history could have been an entire book in itself…

It also gets a *little* bit too religious for me in places (especially at the end)…..but that doesn’t take much! And it’s mainly due to the presentation of some of the views of current scientists, so I’ll let it off 🙂

ai2I also read Artificial Intelligence – A Beginners Guide by Blay Whitby. It is very basic, but quite nicely written. My main liking of this book came from the fact that it explained the current divided state of the research field into distinct ‘camps’, groups of people that all believe their particular specialization is the true discipline, and explains some of the disagreements between them. It was very easy reading, and a nice introduction to some of the main concepts, but I think I definitely want something more mathematical in this area too. Luckily there’s a good selection of recommended further reading!

Interesting recent papers

  • Space-Efficient Simulation of Quantum Computers
  • and quite a bit of stuff about quantum algorithms lately:

  • A Quantum Adiabatic Algorithm for Factorization and Its Experimental Implementation
  • Polynomial-time quantum algorithms for the simulation of chemical dynamics
  • Quantum algorithm for solving linear systems of equations
  • A quantum algorithm to solve nonlinear differential equations
  • Via arXivblog:

  • Dephasing of entangled atoms as an improved test of quantum gravity – I look forward to seeing the results of such an experiment!
  • Future technology

    Some food for thought over Christmas and the new year:
    A few things I’d love to see developed in the future (organised in rough order of near-far future):

    1.) Quantum Computers. Obviously. I believe we’re already well on the way to this goal 😀 And everything that comes with that development… quantum simulation, bio apps, problem solving, and hopefully answering some deep TCS questions along the way.

    2.) A good, lightweight, hi-res Head-Up Display (HUD) for access to the internet (and more) on the move. The best I’ve managed so far is a EeePC and a mobile broadband dongle. Good for coffeeshops and train journeys, but not exactly the ‘information on the move’ technology as portrayed in some sci-fi (e.g. the ‘glasses’ in Charles Stross’s Accelerando)

    3.) Smart materials, which control the environment surrounding the human body in a way similar to the Stillsuit from Dune, recycling waste, regulating temperature, harvesting waste heat energy to (possibly?) power small mobile computing devices and the suit itself. The clothing could perhaps give you health status updates too.

    4.) Commonplace space flights for the general public, a la Virgin Galactic. I’d love to go into space at least once in my lifetime. We’re going to have to move into space when we make the transition to a Type I civilisation anyway, so we might as well get used to the idea now.

    5.) Some form of personal flight device – like this SKYCAR. Although personally I favour more natural wings. Whilst human-powered ornithopters are probably impossible, some form of machine-powered personal ornithopter would be rather cool. (Anyone who knows me will know I have a minor obsession with wings).

    6.) Computing systems with (presumably parallel) processing power similar to that of the human brain, just to have some neat hardware for artificial intelligence research. I’m personally (currently) a proponent of the STRONG AI viewpoint (apologies to Roger Penrose), and I’d love to see systems with our level of intelligence developed on alternate (non-meat based) platforms.

    7.) Brain-Computer interfacing (BCI) – direct upload and download of signals to the brain from an on-body or desktop computer. This also relates to point 2.) in that you could have the HUD as a direct feed to the visual cortex. In combination with point 6.), I like the idea of downloading the instantaneous ‘state’ of the brain (including the neural ‘wiring’ schematic) and and seeing if it can be ‘written’ to a brain with the same physical hardware configuration, and then observing the behaviour of the ‘artificial’ brain.

    I may add to the list if I think of anything else 🙂

    Bubbles in the blogosphere

    A slightly confusing site I must admit, Alpha Inventions seems to have caught the interest of the blogosphere lately.

    The main idea seems to be to display the frontpage of a blog, and every few seconds cycle to a new blog. If the viewer wishes, they can click on a displayed blog. A blog is more likely to be displayed if a.) The blogger writes a post about Alpha Inventions, (I believe that this is equivalent to having hits directed to the site from your own blog) or b.) if the URL of a blog post is entered into an input box on the Alpha Inventions site. In the absence of either of these things happening, (which grows increasingly unlikely as the site becomes more popular), the site also seems to search out and display some blogs randomly.

    Point “a.)” was assertained by visiting the site via my own blog, without having posted anything specifically relating to the site (until now), and then noting the subsequent rise in pageview stats. It should be noted that the hits only seem to be to the frontpage, with very little ‘browsing’ within the blog (e.g. no effect on individual post stats, clicks from within the blog by visitors, or comments). I wonder if the act of displaying the blog itself on Alpha Inventions counts as a ‘hit’ – although the developer claims that this is not the case.

    I’m not sure how this will work in the long term as more and more blogs are added to the queue/list/whatever. The site will presumably become saturated.

    I’m a bit skeptical about the site, as I have personally found it a rather simple process in the past to find blogs which are relevant to my own areas of interest/research, using Technocrati etc., and by browsing other people’s blogrolls. At the moment Alpha Inventions has no search or weighting functions, so you’re most likely to come across a large number of blogs irrelevant to your own interests (which indeed I have).

    The other thing the site seems very good at is creating discontinuities in pageview statistics. Not necessarily a good thing for anyone interested in monitoring ‘natural blogosphere growth’, or sporting a borderline OCD.

    Pnictides: They’re not cuprates…

    People have recently been pondering over the symmetry of the order parameter in the newly discovered (iron-based) pnictide superconductors. Being layered materials, like the cuprates, it was thought that they might be d-wave. However, there is some theoretical basis to them being s-wave, see here and here (Parental Advisory: contains explicit band structure calculations).

    Well, here’s the usual experimental way of settling this matter:

    Phase-Sensitive measurements on the corner junction of iron-based superconductor BaFe1.8Co0.2As2.

    I thought that this might be done soon. See here and here for some early examples of this (rather beautiful) experiment involving YBCO.

    (Picture © Van Harlingen 1995)

    The basis of the method involves making a tunnel junction using a ‘corner’ of a piece of the superconductor of interest. The corner encompasses tunnel directions along both the a and b crystal axes. The other side of the junction is a superconductor which is known to have a direction-independent order parameter symmetry, such as Pb. If the order parameter changes phase with respect to crystal direction, there is a built in phase shift across the junction, which manifests as a shift in the Fraunhofer-type diffraction pattern of the critical current with respect to applied field.

    They conclude that the superconductor is probably s-wave (or at least MOSTLY s-wave). No more yummy pi-junction candidates yet then.

    I love the last line of the paper:

    “This indicates that the superconducting wavefunction of
    the iron based superconductor is definitely not like that of a
    cuprate superconductor.”

    [EDIT 19/12/08] Here is another related paper

    Experimentalist friendly QC books

    I’ve just picked up a copy of this book from the library:


    So far it’s looking quite good. I like it because of the large section in the later chapters dedicated to summarizing the field of experimental progress, whilst still maintaining a thorough introduction to the quantum mechanics, algebra and algorithms. The book covers NMR schemes, trapped ions, atomic (optical lattice) systems, Josephson junction and quantum dot realizations. It is also fairly up to date, being published earlier this year, which is always a bonus 🙂

    Made me wonder though, I haven’t seen any published books (or sections of books) on AQC, or in fact books on schemes other than gate-model based systems, like cluster state or topological QC. I guess some of these fields are young compared to the gate model. Maybe there will be books soon…

    If anyone knows of any such books, please feel free to point them out to me!

    Bio-inspired massively parallel computation

    I attended a Computer Science seminar yesterday given by Professor Steve Furber (see here also) of Manchester University (he helped design the BBC Micro and the ARM microprocessor – which can be found in many mobile phones and other portable devices.)

    The seminar was about taking inspiration from the architecture of the brain to help design new types of parallel processors. The brain is very efficient in terms of energy used per computation, (better by a factor of a million than current microprocessors). Furber argued that transistors are now so cheap that they can be considered an unlimited resource, and the ‘cost’ consideration of increasing processing power is now limited by the energy cost per computation. The brain is also exceptionally fault tolerant considering the number of neurons (~1E11-1E12), it is adaptive, and uses no ‘high performance’ parts – electrically at least, everything operates <100Hz, and at low speeds of transmission between neurons.

    The models that the team are working on, the SpiNNAker project imitates the firing of a ‘data packet’ through a highly connected array of cores, in the same way that the firing of a neuron allows signal transmission by alerting the nearest neighbour neurons to the fact that it has fired. If the packet encounters a broken link, it can reroute. The model is similar to brain architecture in it’s high connectivity of a huge number of simple processing components. The SpiNNAker project hopes to simulate the behaviour of about a billion ‘neurons’ (1% of the human brain, or a whole rat brain!).

    Another argument was that using synchronous algorithms and architectures is not a natural way of computing solutions to asynchronous physical systems, e.g. interacting particles. In the SpiNNaker project, most of the signal transmission (‘neural spiking’) is done asynchronously. Admittedly, the team then do have a lot of problems getting their simulations to ‘talk’ to conventional buses, peripheral ROM etc.

    The brain

    It has been found that the underlying architecture of the brain is similar over the whole of the cortical structure – there is no specialised architecture for different types of task, even though different ‘regions’ within the brain do tend to be adopted for different tasks. It seems over-engineered 🙂 This suggests that if a highly connected ‘building block’ can be scaled up enough, it should potentially mimic the brain, which is exceptionally good at performing high level tasks, e.g. language processing, pattern matching, image recognition, edge detection etc.

    Massively parallel architectures such as the brain are good at these tasks, but (apart from a few exceptions) are not so good at raw data-crunching (multiply/accumulate etc.). I wonder if this is because the architecture fundamentally does not support these kind of calculations very well, or just that the algorithms which convert input signals into computational tasks are not very well developed in the brain for this type of problem. We have no evolutionary need at present to perform large series sums or matrix multiplications to survive.


    I wonder if it is possible to reprogram the brain (artificially) so that it WOULD be good at these low-level problems? Would doing so be detrimental to the higher level functionalilty? I guess the question can be summarised as: Is the type of problem that can be solved efficiently dependent on the architecture in this case?

    I don’t know much about how the brain works out numerical calculations, etc. although I suspect the efficiency of the algorithms that our brain uses for such caluculations is very low. Conversely, we aren’t very good at writing algorithms to run on parallel architectures… but apparently the brain is!

    In a nicely symbiotic way, maybe we can learn something about how the brain works by modelling this class of architecture, and by learning more about the brain, we can understand how to better build massively parallel processors (and how to program them).

    I was slightly disappointed that the seminar made no mention of other models/methods of massively parallel computation (hint, quantum computing, hint) and there seemed to be some confusion amongst the audience between a fundamentally deterministic problem and a non-deterministic problem in the sense of modelling real-world physics but overall I really enjoyed the discussions. Exciting stuff 🙂 I did want to ask the speaker if he believed that the brain behaved as a Turing machine (presumably he does for his project to work), but I didn’t get the chance…

    Anyway as this isn’t really my area I suggest reading more about the project here