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Edward Lorenz, Father of Chaos Theory, Dies at 90
An anonymous reader writes "Professor Edward N. Lorenz, who discovered in 1961 that subtle changes in the initial conditions of a weather simulation program could cause very large differences in its results, died of cancer Wednesday at the age of 90. The contributions of the father of chaos theory, who coined the term 'the butterfly effect' and also discovered the Lorenz Attractor, are best summarized by the wording of the Kyoto Prize in 1991 which noted that his discovery of chaos theory 'profoundly influenced a wide range of basic sciences and brought about one of the most dramatic changes in mankind's view of nature since Sir Isaac Newton.'"
...and also one that's fun to play with (needs java).
As humor is often just a funny way of being serious, I don't think it's too soon for jokes.
Perhaps we should all use one of the many chaos generators out there for a few minutes as a way to salute his work? What is the best chaos program out there nowadays - I haven't used one since fractint ages ago. Well I did install the electric sheep screen saver which is very nice eye candy, but I want to see some particles circling around a lorenz attractor.
And it would be warranted. The 'butterfly effect' is a horribly misleading statement. Mathematical chaos applies to only certain deterministic systems, not real life. There is no evidence that the real world is a simulation or even if it was that it falls into the narrow range of non-linear dynamics problems that exhibit mathematical chaos. Lorenz's attempt at modeling the weather certainly exhibited mathematical chaos, but the model wasn't the weather itself.
Back in my college days, I visited the library and looked up Lorenz's paper, "Deterministic Nonperiodic Flow." On the face of it, the presentation was not particularly striking, nor did it seem significant on a superficial reading. That it was buried in a meteorology journal, rather than a mathematics or physics journal, only further obscured its importance.
Lorenz's discovery was not so much about the specific nonlinear differential system (now named after him) that he discussed in the paper, nor was it about chaos theory as we now know it. The significance lay entirely in the notion that even simple dynamical systems can display sensitive dependence on initial conditions, and that when extrapolated to real-world phenomena, the intrinsic complexity of their behavior was all but inevitable.
A chaotic system is not merely disordered, or random. There is an underlying structure. Call it a kind of orderly disorder. Prior to (and indeed, for some time after) Lorenz's work, physicists largely dismissed this possibility as absurd. We can, in such a system, model its state at some infinitesimal time t+dt after some given state at time t. We can do this quite accurately. But as Lorenz showed, the deterministic property is insufficient to imply that one can know the state of the system at any arbitrary time in the future. There is a difference between knowing how the future is calculated from the past, versus knowing what the future will actually be.
Hence the chosen title. "Deterministic" = future states are well-defined from a known prior state. "Nonperiodic" = does not display cyclical behavior. "Flow" = fluid dynamics, in Lorenz's case, atmospheric convection.
He is truly missed.
Andy
Chaos: The Making of a New Science. Tells the entire story of Lorentz's discovery, in gory detail, down to the fact that he used a Royal McBee computer to do his original weather simulation, the same computer in the famous hacker "Story of Mel".
Don't blame me, I voted for Baltar.
> ... it is controversial that chaos will ever ... there are
> contribute to science in any way.
> a lot of bad papers purporting to use chaos
> theory.
From my own field:
Supporting your assertion -- A characterization of chaos is measuring the fractional (ie. 'fractal') dimensionality of the phenomenon. Someone estimated the dimension of the human cortex, with its convolutions embedded within convolutions. They plugged in numbers and got a result. But what's the point? What good does it do? There's no theory of even speculation as to what this might mean. It's doing 'sexy' but irrelevant science.
Contrary to your assertion -- EEG shows signs of being chaotic (self-similarity at different scales, dependence on initial conditions). Characterizing the dynamics (changing dimensionality) of the bioelectric field at different scales was compared with the same measure of synchronous firing of neural assemblies. The result significantly supported the hypothesis that EEG at different scales represented changes in neural synchrony/desynchrony at different scales. The synchrony concept is trivial, and well supported by electrophysiological measurement. This application showed that characterizing the signal as chaotic (and so too the deterministic phenomenon producing it) had some validity. The utility of the study applies to use of transcranial magnetic stimulation to force widespread synchronus firing, reducing the dimensionality, and forcing a state also having low D, that of people with depression taking antidepressants and showing benefit from them. It supports the hypothesis that TMS can treat depression. And it now does.
With respect to my field, you're mostly correct in your assertion. Most applications are quite obviously being done by people with little understanding of the concepts, and/or applied to things with little regard as to whether it makes sense to do so.
> Its controversial that [Lorenz] was the first.
Quite so. He did, however, investigate the nature of what he was seeing in a very creditable way. After noting the sensitivity to initial conditions, he reran one of his simulations from the middle, expecting it to finish out the run producing the same data. It didn't. And he took that to be a significant (in the practical sense) result, despite it being contrary to his expectations. Many researchers would bottom-drawer a dataset that contradicted their hypotheses. He recognized the probability that it would prove important. That takes some courage as a researcher, and he deserves credit for that at least.
"I may be synthetic, but I'm not stupid." -- Bishop 341-B