Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. Quantum tunneling provides a different mechanism for moving between states, with the potential for reduced time scales and different outcomes. Thermal and quantum annealing are compared in two concentration regimes of a model disordered magnet, where the effects of quantum mechanics can be tuned both by varying an applied magnetic field and by controlling the strength of thermal coupling between the magnet and an external heat bath. The results indicate that quantum annealing hastens convergence to the final state, and that the quantum character of the final state can be engineered thermodynamically
Quantum annealers aim at solving nonconvex optimization problems by exploiting cooperative tunneling...
Recent experiments with increasingly larger numbers of qubits have sparked renewed interest in adiab...
Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Quantum annealing is analogous to simulated annealing with a tunneling mechanism substituting for th...
We review here some recent work in the field of quantum annealing, alias adiabatic quantum computati...
Quantum annealing was recently found experimentally in a disordered spin-1/2 magnet to be more effec...
Probing the lowest energy configuration of a complex system by quantum annealing was recently found ...
In this review we consider the performance of the quantum adiabatic algorithm for the solution of de...
We introduce and review briefly the phenomenon of quantum annealing and analog computation. The role...
One of the major ongoing debates on the future of quantum annealers pertains to their robustness aga...
Quantum annealers aim at solving nonconvex optimization problems by exploiting cooperative tunneling...
Recent experiments with increasingly larger numbers of qubits have sparked renewed interest in adiab...
Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
Quantum annealing is analogous to simulated annealing with a tunneling mechanism substituting for th...
We review here some recent work in the field of quantum annealing, alias adiabatic quantum computati...
Quantum annealing was recently found experimentally in a disordered spin-1/2 magnet to be more effec...
Probing the lowest energy configuration of a complex system by quantum annealing was recently found ...
In this review we consider the performance of the quantum adiabatic algorithm for the solution of de...
We introduce and review briefly the phenomenon of quantum annealing and analog computation. The role...
One of the major ongoing debates on the future of quantum annealers pertains to their robustness aga...
Quantum annealers aim at solving nonconvex optimization problems by exploiting cooperative tunneling...
Recent experiments with increasingly larger numbers of qubits have sparked renewed interest in adiab...
Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable ...