Physics successfully implements Lagrange multiplier optimization

Abstract

All through human civilization, optimization has played a major role, from aerodynamics to airline scheduling, delivery routing, and telecommunications decoding. Optimization is receiving increasing attention, since it is central to today’s artificial intelligence. All of these optimization problems are among the hardest for human or machine to solve. It has been overlooked that physics itself does optimization in the normal evolution of dynamical systems, such as seeking out the minimum energy state. We show that among such physics principles, the idea of minimum power dissipation, also called the Principle of Minimum Entropy Generation, appears to be the most useful, since it can be readily implemented in electrical or optical circuits.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 12, 2020
Source ID
10.1073/pnas.2015192117

Entities

People

  • Eli Yablonovitch
  • Sri Krishna Vadlamani
  • Tianyao Patrick Xiao

Organizations

  • National Science Foundation
  • Office of Naval Research
  • Sandia National Laboratories

Tags

Fields of Study

  • Physics

Readers

  • Economics
  • Operations Research
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms