2006/08/18 by Giuseppe E. Santoro, Erio Tosatti · 15 citations
Computer Science · Physics and Astronomy · #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #Quantum annealing #Adiabatic process #Quantum #Quantum mechanics #Physics #Quantum dynamics #Statistical physics #Quantum dissipation #Adiabatic quantum computation #Classical mechanics #Quantum computer
paper · pdf · doi:10.1088/0305-4470/39/36/r01
openalex publication_date 2006/08/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We review here some recent work in the field of quantum annealing, alias adiabatic quantum computation. The idea of quantum annealing is to perform optimization by a quantum adiabatic evolution which tracks the ground state of a suitable time-dependent Hamiltonian, where 'ℏ' is slowly switched off. We illustrate several applications of quantum annealing strategies, starting from textbook toy-models—double-well potentials and other one-dimensional examples, with and without disorder. These examples display in a clear way the crucial differences between classical and quantum annealing. We then discuss applications of quantum annealing to challenging hard optimization problems, such as the random Ising model, the travelling salesman problem and Boolean satisfiability problems. The techniques used to implement quantum annealing are either deterministic Schrödinger's evolutions, for the toy models, or path-integral Monte Carlo and Green's function Monte Carlo approaches, for the hard optimization problems. The crucial role played by disorder and the associated non-trivial Landau–Zener tunnelling phenomena is discussed and emphasized.