We study quantum annealing for combinatorial optimization with Hamiltonian $H = z H_f + H_0$ where $H_f$ is diagonal, $H_0=-|\phi \rangle \langle \phi|$ is the equal superposition state projector and $z$ the annealing parameter. We analytically compute the minimal spectral gap as $\mathcal{O}(1/\sqrt{N})$ with $N$ the total number of states and its location $z_*$. We show that quantum speed-up requires an annealing schedule which demands a precise knowledge of $z_*$, which can be computed only if the density of states of the optimization problem is known. However, in general the density of states is intractable to compute, making quadratic speed-up unfeasible for any practical combinatoric optimization problems. We conjecture that it is lik...
Quantum annealing aims at finding optimal solutions to complex optimization problems using a suitabl...
We provide a reusability report of the method presented by Chen et al. in "Optimizing quantum anneal...
Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions ...
We introduce and review briefly the phenomenon of quantum annealing and analog computation. The role...
In this review, after providing the basic physical concept behind quantum annealing (or adiabatic qu...
We perform an in-depth comparison of quantum annealing with several classical optimisation technique...
We study adiabatic reverse annealing (ARA) in an open system. In the closed system (unitary) setting...
In adiabatic quantum annealing the required run-time to reach a given ground-state fidelity is dicta...
In recent years, quantum annealing has gained the status of being a promising candidate for solving ...
Can quantum computers solve optimization problems much more quickly than classical computers? One ma...
Quantum annealing (QA) is a promising approach for not only solving combinatorial optimization probl...
Can quantum computers solve optimization problems much more quickly than classical computers? One ma...
Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a g...
Abstract. Discrete combinatorial optimization consists in finding the optimal configuration that min...
The observation of an unequivocal quantum speedup remains an elusive objective for quantum computing...
Quantum annealing aims at finding optimal solutions to complex optimization problems using a suitabl...
We provide a reusability report of the method presented by Chen et al. in "Optimizing quantum anneal...
Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions ...
We introduce and review briefly the phenomenon of quantum annealing and analog computation. The role...
In this review, after providing the basic physical concept behind quantum annealing (or adiabatic qu...
We perform an in-depth comparison of quantum annealing with several classical optimisation technique...
We study adiabatic reverse annealing (ARA) in an open system. In the closed system (unitary) setting...
In adiabatic quantum annealing the required run-time to reach a given ground-state fidelity is dicta...
In recent years, quantum annealing has gained the status of being a promising candidate for solving ...
Can quantum computers solve optimization problems much more quickly than classical computers? One ma...
Quantum annealing (QA) is a promising approach for not only solving combinatorial optimization probl...
Can quantum computers solve optimization problems much more quickly than classical computers? One ma...
Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a g...
Abstract. Discrete combinatorial optimization consists in finding the optimal configuration that min...
The observation of an unequivocal quantum speedup remains an elusive objective for quantum computing...
Quantum annealing aims at finding optimal solutions to complex optimization problems using a suitabl...
We provide a reusability report of the method presented by Chen et al. in "Optimizing quantum anneal...
Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions ...