136 citations · 513 across the 37 of their papers we have counts for
5 papers · 2 filters
Parallel Quantum Annealing
Elijah Pelofske, Georg Hahn, Hristo N. Djidjev
Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions of NP-hard problems. This is done by mapping a problem onto the physical qubits…
Quantum Annealing Algorithms for Boolean Tensor Networks
Elijah Pelofske, Georg Hahn, Daniel O'Malley +2
Quantum annealers manufactured by D-Wave Systems, Inc., are computational devices capable of finding high-quality solutions of NP-hard problems. In this contribution, we explore th…
Using machine learning for quantum annealing accuracy prediction
Aaron Barbosa, Elijah Pelofske, Georg Hahn +1
Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a way to compute solutions of NP-hard problems that can be expressed in Ising or QUBO (quadratic unconstr…
Boolean Hierarchical Tucker Networks on Quantum Annealers
Elijah Pelofske, Georg Hahn, Daniel O'Malley +2
Quantum annealing is an emerging technology with the potential to solve some of the computational challenges that remain unresolved as we approach an era beyond Moore's Law. In thi…
Reducing quantum annealing biases for solving the graph partitioning problem
Elijah Pelofske, Georg Hahn, Hristo N. Djidjev
Quantum annealers offer an efficient way to compute high quality solutions of NP-hard problems when expressed in a QUBO (quadratic unconstrained binary optimization) or an Ising fo…