In this paper, the maze generation using quantum annealing is proposed. We reformulate a standard algorithm to generate a maze into a specific form of a quadratic unconstrained binary optimization problem suitable for the input of the quantum annealer. To generate more difficult mazes, we introduce an additional cost function $Q_{update}$ to increase the difficulty. The difficulty is evaluated by the time to solve the maze. To check the efficiency of our scheme to create the maze, we investigated the time-to-solution of a quantum processing unit, classical computer, and hybrid solver.Comment: 14pages, 12figure
Quantum annealing is a heuristic quantum optimization algorithm that can be used to solve combinator...
To date, conventional computers have never been able to efficiently handle certain tasks, where the ...
Quantum annealing, or quantum stochastic optimization, is a classical randomized algorithm which pro...
In this paper, the maze generation using quantum annealing is proposed. We reformulate a standard al...
We introduce and review briefly the phenomenon of quantum annealing and analog computation. The role...
Quantum annealing belongs to a family of quantum optimization algorithms designed to solve combinato...
Quantum annealing, a method of computing where optimization and machine learning problems are mapped...
We perform an in-depth comparison of quantum annealing with several classical optimisation technique...
In this thesis, we implement projective quantum Monte Carlo (PQMC) methods to simulate quantum annea...
Providing an optimal path to a quantum annealing algorithm is key to finding good approximate soluti...
Ising machines have the potential to realize fast and highly accurate solvers for combinatorial opti...
Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions ...
© 2016 IEEE. Can quantum computers solve optimization problems much more quickly than classical comp...
© 2016 IEEE. Can quantum computers solve optimization problems much more quickly than classical comp...
Quantum annealing is a heuristic algorithm for searching the ground state of an Ising model. Heurist...
Quantum annealing is a heuristic quantum optimization algorithm that can be used to solve combinator...
To date, conventional computers have never been able to efficiently handle certain tasks, where the ...
Quantum annealing, or quantum stochastic optimization, is a classical randomized algorithm which pro...
In this paper, the maze generation using quantum annealing is proposed. We reformulate a standard al...
We introduce and review briefly the phenomenon of quantum annealing and analog computation. The role...
Quantum annealing belongs to a family of quantum optimization algorithms designed to solve combinato...
Quantum annealing, a method of computing where optimization and machine learning problems are mapped...
We perform an in-depth comparison of quantum annealing with several classical optimisation technique...
In this thesis, we implement projective quantum Monte Carlo (PQMC) methods to simulate quantum annea...
Providing an optimal path to a quantum annealing algorithm is key to finding good approximate soluti...
Ising machines have the potential to realize fast and highly accurate solvers for combinatorial opti...
Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions ...
© 2016 IEEE. Can quantum computers solve optimization problems much more quickly than classical comp...
© 2016 IEEE. Can quantum computers solve optimization problems much more quickly than classical comp...
Quantum annealing is a heuristic algorithm for searching the ground state of an Ising model. Heurist...
Quantum annealing is a heuristic quantum optimization algorithm that can be used to solve combinator...
To date, conventional computers have never been able to efficiently handle certain tasks, where the ...
Quantum annealing, or quantum stochastic optimization, is a classical randomized algorithm which pro...