Quantum annealing is a quantum algorithm proposed recently for combinatorial optimization problems. It manipulates time evolution of a quantum mechanical state and obtain an approximate solution. In order to implement the algorithm in classical computers, we propose to apply the density matrix renormalization group method. Simulation of the time evolution of a quantum mechanical state becomes possible by the density matrix renormalization group method for problems of large size. We explain quantum annealing and the density matrix renormalization group method, and present results of numerical simulation using them
Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a g...
In many real-life situations in engineering (and in other disciplines), we need to solve an optimiza...
Abstract. Discrete combinatorial optimization consists in finding the optimal configuration that min...
Quantum annealing, or quantum stochastic optimization, is a classical randomized algorithm which pro...
We briefly review various computational methods for the solution of optimization problems. First, se...
Abstract. We briefly review various computational methods for the solution of optimization problems....
"Quantum annealing employs quantum fluctuations in frustrated systems or networks to anneal the syst...
The focus of this work is an implementation of the chosen quantum-inspired optimisation algorithm an...
Quantum annealing belongs to a family of quantum optimization algorithms designed to solve combinato...
Quantum annealing is a new-generation tool of information technology, which helps in solving combina...
Quantum annealing is a quantum computing approach widely used for optimization and probabilistic sam...
We review here some recent work in the field of quantum annealing, alias adiabatic quantum computati...
Quantum annealing is analogous to simulated annealing with a tunneling mechanism substituting for th...
The path integral Monte Carlo simulated quantum annealing algorithm is applied to the optimization o...
In this study, we simulated a quantum annealing process at zero and finite tem-perature by using ...
Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a g...
In many real-life situations in engineering (and in other disciplines), we need to solve an optimiza...
Abstract. Discrete combinatorial optimization consists in finding the optimal configuration that min...
Quantum annealing, or quantum stochastic optimization, is a classical randomized algorithm which pro...
We briefly review various computational methods for the solution of optimization problems. First, se...
Abstract. We briefly review various computational methods for the solution of optimization problems....
"Quantum annealing employs quantum fluctuations in frustrated systems or networks to anneal the syst...
The focus of this work is an implementation of the chosen quantum-inspired optimisation algorithm an...
Quantum annealing belongs to a family of quantum optimization algorithms designed to solve combinato...
Quantum annealing is a new-generation tool of information technology, which helps in solving combina...
Quantum annealing is a quantum computing approach widely used for optimization and probabilistic sam...
We review here some recent work in the field of quantum annealing, alias adiabatic quantum computati...
Quantum annealing is analogous to simulated annealing with a tunneling mechanism substituting for th...
The path integral Monte Carlo simulated quantum annealing algorithm is applied to the optimization o...
In this study, we simulated a quantum annealing process at zero and finite tem-perature by using ...
Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a g...
In many real-life situations in engineering (and in other disciplines), we need to solve an optimiza...
Abstract. Discrete combinatorial optimization consists in finding the optimal configuration that min...