Metastable Dynamical Computing with Energy Landscapes: A Primer
Christian Z. Pratt, Kyle J. Ray, James P. Crutchfield

TL;DR
This paper introduces metastable dynamical computing using energy landscapes, demonstrating how potential minima can serve as memory states for energy-efficient information processing and logic gate design.
Contribution
It presents a novel framework linking energy landscape manipulation with thermodynamic computation, including analysis of fixed points and experimental demonstrations of logic gates.
Findings
Demonstrated 1-bit and 2-bit computations using potential wells.
Showed how metastable states encode information.
Analyzed thermodynamic efficiency of logic operations.
Abstract
Smartphones, laptops, and data centers are CMOS-based technologies that ushered our world into the information age of the 21st century. Despite their advantages for scalable computing, their implementations come with surprisingly large energetic costs. This challenge has revitalized scientific and engineering interest in energy-efficient information-processing designs. One current paradigm -- dynamical computing -- controls the location and shape of minima in potential energy landscapes that are connected to a thermal environment. The landscape supports distinguishable metastable energy minima that serve as a system's mesoscopic memory states. Information is represented by microstate distributions. Dynamically manipulating the memory states then corresponds to information processing. This framing provides a natural description of the associated thermodynamic transformations and required…
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Taxonomy
TopicsNeural Networks and Reservoir Computing · Advanced Memory and Neural Computing · Advanced Thermodynamics and Statistical Mechanics
