Solid State Technology and Devices Seminar: Analog Physics for Digital Optimization

Seminar: Solid State Technology and Devices: EE: CS | November 15 | 1-2 p.m. | Cory Hall, The Hogan Room, 521

 Sri Krishna Vadlamani, Ph.D. Student and Researcher, Electrical Engineering and Computer Sciences Dept. University of California

 Electrical Engineering and Computer Sciences (EECS)

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

In effect, Physics can provide analog machines which solve digital optimization problems much faster than any digital computer. Of these physics principles, “Minimum Entropy Generation” in the form of bistable analog electrical or optical circuits is particularly adaptable toward offering digital Optimization. As an example, we provide an analog electrical circuit which can address the challenging Ising problem, binary magnet energy minimization.

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