Engine of Computation

Chaotic systems are extremely sensitive to the initial conditions and parameters that define them. Minute perturbations of the parameters can even convert chaotic motion to periodic motion. This alliance between control methods and physics — cybernetical physics — opens the door to many applications, including dynamics-based computing. We recently published an article that introduces nonlinear dynamics and its rich, sometimes chaotic behavior as an engine of computation. After reviewing our previous work demonstrating how to compute using nonlinear dynamics, we describe the interrelationship between invariant measures of a dynamical system and its computing power to strengthen the bridge between physics and computation.

Our article was published in the Philosophical Transactions of the Royal Society, the world’s first and oldest science journal, which previously published work by Isaac Newton, Michael Faraday, and James Clerk Maxwell. Of course, no comparison between our work and theirs is intended, except via a logarithmic scale. 🙂

Title page of volume 1 of the Philosophical Transactions of the Royal Society, the world's first and oldest science journal

Title page of volume 1 of the Philosophical Transactions of the Royal Society, the world’s first and oldest science journal

About John F. Lindner

John F. Lindner was born in Sleepy Hollow, New York, and educated at the University of Vermont and Caltech. He is an emeritus professor of physics and astronomy at The College of Wooster and a visiting professor at North Carolina State University. He has enjoyed multiple yearlong sabbaticals at Georgia Tech, University of Portland, University of Hawai'i, and NCSU. His research interests include nonlinear dynamics, celestial mechanics, and neural networks.
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