Optical physics does digital optimization—which we call Onsager Computing—for machine learning, control theory, backpropagation, etc.

Eli Yablonovitch; Sri Vadlamani

doi:10.1117/12.2617214

5 March 2022 Optical physics does digital optimization—which we call Onsager Computing—for machine learning, control theory, backpropagation, etc.

Eli Yablonovitch, Sri Vadlamani

Author Affiliations +

Proceedings Volume PC12005, Smart Photonic and Optoelectronic Integrated Circuits 2022; PC120050C (2022) https://doi.org/10.1117/12.2617214
Event: SPIE OPTO, 2022, San Francisco, California, United States

Abstract

Optimization is vital to Engineering, Artificial Intelligence, and to many areas of Science. Mathematically, we usually employ steepest-descent, or other digital algorithms. But, Physics itself, performs optimizations in the normal course of dynamical evolution. Nature provides us with the following optimization principles: 1. The Principle of Least Action; 2. The Variational Principle of Quantum Mechanics; 3. The Principle of Minimum Entropy Generation; 4. The First Mode to Threshold method; 5. The Principle of Least Time; 6. The Adiabatic Evolution method; 7. Quantum Annealing Of these physics principles, “Minimum Entropy Generation” in the form of bistable electrical or optical circuits is particularly adaptable toward offering digital Optimization. For example, we provide the electrical circuit which can address the challenging Ising problem. Since Onsager, 1930, introduced the Principle of Minimum Entropy Generation we call this Onsager Computing.

Conference Presentation

Citation Download Citation

Eli Yablonovitch and Sri Vadlamani "Optical physics does digital optimization—which we call Onsager Computing—for machine learning, control theory, backpropagation, etc.", Proc. SPIE PC12005, Smart Photonic and Optoelectronic Integrated Circuits 2022, PC120050C (5 March 2022); https://doi.org/10.1117/12.2617214

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