Quantum annealing (QA) is a
metaheuristic for finding the
global minimum of a given
objective function over a given set of candidate solutions (candidate states), by a process using
quantum fluctuations. Quantum annealing is used mainly for problems where the search space is discrete (
combinatorial optimization problems) with many
local minima; such as finding the
ground state of a
spin glass. It was formulated in its present form by T. Kadowaki and H. Nishimori in "Quantum annealing in the transverse Ising model" though a proposal in a different form had been proposed by A. B. Finilla, M. A. Gomez, C. Sebenik and J. D. Doll, in "Quantum annealing: A new method for minimizing multidimensional functions".