Sri Krishna Vadlamani
Optimization is built into the fundamentals of physics. For example, physics has the principle of least action, the principle of minimum power dissipation, also called minimum entropy generation, and the adiabatic principle, which, in its quantum form, is called quantum annealing. Machines built on these principles can solve the mathematical problem of optimization, even when constraints are included. Further, these machines become digital, in the same sense that a flip–flop is digital, when binary constraints are included. A wide variety of machines, including coupled driven dissipative electrical oscillators, coupled exciton-polariton condensates, and others, have had recent success at optimizing the Ising magnetic energy. We demonstrate that almost all those machines perform optimization according to the principle of minimum power dissipation as put forth by Onsager. Further, we show that this optimization is in fact equivalent to Lagrange multiplier optimization for constrained problems.