Skip to search formSkip to main contentSemantic Scholar

You are currently offline. Some features of the site may not work correctly.

Semantic Scholar uses AI to extract papers important to this topic.

Highly Cited

2018

Highly Cited

2018

In this work we perform numerical simulations of a quantum annealing procedure to find the ground state of a target Hamiltonian… Expand

Is this relevant?

Highly Cited

2017

Highly Cited

2017

Quantum annealing algorithms belong to the class of meta-heuristic tools, applicable for solving binary optimization problems… Expand

Is this relevant?

2017

2017

I describe how real quantum annealers may be used to perform local (in state space) searches around specified states, rather than… Expand

Is this relevant?

Highly Cited

2016

Highly Cited

2016

Inspired by the success of Boltzmann Machines based on classical Boltzmann distribution, we propose a new machine learning… Expand

Is this relevant?

2016

2016

Can quantum computers solve optimization problems much more quickly than classical computers? One major piece of evidence for… Expand

Is this relevant?

Highly Cited

2014

Highly Cited

2014

Quantum annealing is expected to solve certain optimization problems more efficiently, but there are still open questions… Expand

Is this relevant?

Highly Cited

2014

Highly Cited

2014

Abstract : Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable by classical… Expand

Is this relevant?

Highly Cited

2014

Highly Cited

2014

Recently, a programmable quantum annealing machine has been built that minimizes the cost function of hard optimization problems… Expand

Is this relevant?

Highly Cited

2011

Highly Cited

2011

Quantum annealing extends simulated annealing by introducing artificial quantum fluctuations. The path-integral Monte Carlo… Expand

Is this relevant?

Highly Cited

1998

Highly Cited

1998

We introduce quantum fluctuations into the simulated annealing process of optimization problems, aiming at faster convergence to… Expand

Is this relevant?