Quantum Annealing

Quantum annealing is a restricted model of quantum computing built specifically for optimization problems rather than general-purpose algorithms. An optimization problem is first mapped onto a physical system of qubits so that the system's lowest-energy configuration (its ground state) corresponds to the best solution. The qubits start in an easy-to-prepare state and are evolved slowly, guided by the adiabatic theorem, which states that a quantum system starting in its ground state stays in the ground state if the evolution is slow enough, toward the problem's energy landscape, so that measuring the qubits at the end reads out a low-energy, hopefully optimal, solution. D-Wave is the dominant commercial vendor of quantum annealing hardware, with systems exceeding 5,000 qubits, though annealing qubits are not directly comparable to the gate-model qubits used by IBM, Google, or IonQ, since annealers cannot run arbitrary circuits like Grover's or Shor's algorithm. Whether quantum annealers deliver a real speedup over the best classical optimization heuristics on practical problems remains genuinely contested and appears to depend heavily on the specific problem structure.