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Quantum annealing (QA) is an optimization process 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.
The process can be distinguished from Simulated annealing by the Quantum tunneling process, by which particles tunnel through kinetic or potential barriers from a high state to a low state. Quantum annealing starts from a superposition of all possible states of a system, weighted equally.
Quantum annealing uses "quantum fluctuations" instead of thermal fluctuations to get through high but thin barriers in the target function. Stochastic tunneling attempts to overcome the increasing difficulty simulated annealing runs have in escaping from local minima as the temperature decreases, by 'tunneling' through barriers.
Unlike competitors that initially focused on general-purpose quantum computers, D-Wave developed quantum annealing systems specifically designed for optimization problems. Since the mid-2010s ...
Adiabatic quantum computation (AQC) is a form of quantum computing which relies on the adiabatic theorem to perform calculations and is closely related to quantum annealing.
Quantum annealing relies on the adiabatic theorem to undertake calculations. A system is placed in the ground state for a simple Hamiltonian, which slowly evolves to ...
Rigetti's full-stack development approach and superconducting quantum processors provide unique advantages in scaling quantum systems. D-Wave's quantum annealing technology could prove valuable ...
D-Wave focuses on quantum annealing, an alternative processing method it believes delivers practical, real-world advantages for optimization problems. With more than 130 commercial, research, and ...