activity
20132022
most citedNonnegative/binary matrix factorization with a D-Wave quantum annealer

144 citations · 361 across the 19 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

quant-ph2021★ 27 cited

Sampling on NISQ Devices: "Who's the Fairest One of All?"

Elijah Pelofske, John Golden, Andreas Bärtschi +2

Modern NISQ devices are subject to a variety of biases and sources of noise that degrade the solution quality of computations carried out on these devices. A natural question that…

quant-ph2021★ 18 cited

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…

quant-ph2021★ 23 cited

Threshold-Based Quantum Optimization

John Golden, Andreas Bärtschi, Daniel O'Malley +1

We propose and study Th-QAOA (pronounced Threshold QAOA), a variation of the Quantum Alternating Operator Ansatz (QAOA) that replaces the standard phase separator operator, which e…

cs.LG2021★ 1 cited

A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks

Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg +4

This work is the first to employ and adapt the image-to-image translation concept based on conditional generative adversarial networks (cGAN) towards learning a forward and an inve…

quant-ph2021★ 3 cited

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…