Chaotic Physics in Ferroelectrics Hints at Brain-Like Computing

When drawing domains of switched polarization on the surface of a ferroelectric material, researchers realized that chaos had emerged spatially. This opens the possibility of brain-like computing in which information storage and processing occur on the same physical platform.

Unexpected behavior in ferroelectric materials explored by researchers at the Department of Energy's Oak Ridge National Laboratory supports a new approach to information storage and processing.

Ferroelectric materials are known for their ability to spontaneously switch polarization when an electric field is applied. Using a scanning probe microscope, the ORNL-led team took advantage of this property to draw areas of switched polarization called domains on the surface of a ferroelectric material. To the researchers' surprise, when written in dense arrays, the domains began forming complex and unpredictable patterns on the material's surface.

"When we reduced the distance between domains, we started to see things that should have been completely impossible," said ORNL's Anton Ievlev, the first author on the paper published in Nature Physics. "All of a sudden, when we tried to draw a domain, it wouldn't form, or it would form in an alternating pattern like a checkerboard. At first glance, it didn't make any sense. We thought that when a domain forms, it forms. It shouldn't be dependent on surrounding domains."

After studying patterns of domain formation under varying conditions, the researchers realized the complex behavior could be explained through chaos theory. One domain would suppress the creation of a second domain nearby but facilitate the formation of one farther away -- a precondition of chaotic behavior, says ORNL's Sergei Kalinin, who led the study. [emphasis mine]

"Chaotic behavior is generally realized in time, not in space," he said. "An example is a dripping faucet: sometimes the droplets fall in a regular pattern, sometimes not, but it is a time-dependent process. To see chaotic behavior realized in space, as in our experiment, is highly unusual."

Collaborator Yuriy Pershin of the University of South Carolina explains that the team's system possesses key characteristics needed for memcomputing, an emergent computing paradigm in which information storage and processing occur on the same physical platform.

"Memcomputing is basically how the human brain operates: Neurons and their connections--synapses--can store and process information in the same location," Pershin said. "This experiment with ferroelectric domains demonstrates the possibility of memcomputing." [emphasis mine]

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When I was first introduced to Chaos Theory, it seemed to me some things could be explained that otherwise made no sense. For example, reasoning wasn't necessarily linear; early small influences create chaos that result in what is called the "butterfly effect". Once the computer came into being, small effects could be plotted over time after many iterations producing non-linear patterns. Benoit Mandelbrot developed fractal geometry by putting a simple formula into a computer, accidentally left it running overnight, resulting in repeating patterns and changes.

Early on, I tried to replicate what Mendelbrot did with a computer, by doing calculations with pencil and paper. After four or five pages of computations a tiny little pattern begin to form. The computer made the iterations easy.

Self-replicating patterns with small deviations from linear formula produced huge differences with iterations. Along came Daniel Dennett, and his research that demonstrates evolutionary patterns of one cell after many iterations, changed into multi-cell organisms, then into swimming organisms, this all on a computer. It made sense. Small changes over time result in non-linear patterns of great magnitude.

Lorenz's discovery revealed how small changes in temperature, moisture, atmospheric pressure changed weather patterns. As behavioral science students knew, there were all kinds of correlations that could not be explained by linear reasoning. For example there is a very strong correlation between the temperature in New York City and the neo-natal death rate in Nepal. That makes no sense! We know correlation does not mean cause. Why was the correlation so high, over time, and repeated by many scientists. Well, it seems small changes in weather patterns impact both NYC and Nepal. These were two measures that revealed the patterns.

Well, won't go on any further with this re-hash. I just am very intrigued by this report and expect to have more studies explaining what all this means.

That was interesting - thank you Ruth.

My Ornithology professor introduced me to Chaos Theory. I thought it was an interesting concept.


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