Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Bulletin of the American Physical Society

Progress towards a small-scale quantum annealer I: Architecture

Yu Chen, Chris Quintana, Dvir Kafri, Alireza Shabani, B. Chiaro, Brooks Foxen, Zijun Chen, A. Dunsworth, C. Neill, J. Wenner, Hartmut Neven, John M. Martinis

Published Mar 13, 2017• 4 citations
OpenAlex

Related papers

Progress towards a small-scale quantum annealer III: Device theory and modeling

Dvir Kafri, Chris Quintana, Yu Chen +4 more

Bulletin of the American Physical Society•Mar 13, 2017•0 citations

Progress towards a small-scale quantum annealer II: Device characterization and ultra-strong tunable coupling

Chris Quintana, Yu Chen, Dvir Kafri +9 more

Bulletin of the American Physical Society•Mar 13, 2017•0 citations

Towards large-scale superconducting quantum annealers: 2.5D packaging technology and application specific architecture

Shiro Kawabata, Kazuhiko Endo, Go Fujii +19 more

Bulletin of the American Physical Society•Mar 8, 2018•0 citations

Progress Towards Quantum Annealer v2.0 II: Theory

Dvir Kafri, Chris Quintana, Yu Chen +2 more

Bulletin of the American Physical Society•Mar 5, 2018•0 citations

Seeking Quantum Speedup Through Spin Glasses: The Good, the Bad, and the Ugly

Helmut G. Katzgraber, Firas Hamze, Zhu, Zheng +2 more

There has been considerable progress in the design and construction of quantum annealing devices. However, a conclusive detection of quantum speedup over traditional silicon-based machines remains elusive, despite multiple careful studies. In this work we outline strategies to design hard tunable benchmark instances based on insights from the study of spin glasses - the archetypal random benchmark problem for novel algorithms and optimization devices. We propose to complement head-to-head scaling studies that compare quantum annealing machines to state-of-the-art classical codes with an approach that compares the performance of different algorithms and/or computing architectures on different classes of computationally hard tunable spin-glass instances. The advantage of such an approach lies in having to only compare the performance hit felt by a given algorithm and/or architecture when the instance complexity is increased. Furthermore, we propose a methodology that might not directly translate into the detection of quantum speedup, but might elucidate whether quantum annealing has a "`quantum advantage" over corresponding classical algorithms like simulated annealing. Our results on a 496 qubit D-Wave Two quantum annealing device are compared to recently-used state-of-the-art thermal simulated annealing codes.

•Jan 1, 2015•86 citations

2. Quantum Annealer, its Potential and Perspective

Masayuki Ohzeki

The Journal of The Institute of Image Information and Television Engineers•Jan 1, 2019•0 citations
There has been considerable progress in the design and construction of quantum annealing devices. However, a conclusive detection of quantum speedup over traditional silicon-based machines remains elusive, despite multiple careful studies. In this work we outline strategies to design hard tunable benchmark instances based on insights from the study of spin glasses - the archetypal random benchmark problem for novel algorithms and optimization devices. We propose to complement head-to-head scaling studies that compare quantum annealing machines to state-of-the-art classical codes with an approach that compares the performance of different algorithms and/or computing architectures on different classes of computationally hard tunable spin-glass instances. The advantage of such an approach lies in having to only compare the performance hit felt by a given algorithm and/or architecture when the instance complexity is increased. Furthermore, we propose a methodology that might not directly translate into the detection of quantum speedup, but might elucidate whether quantum annealing has a "`quantum advantage" over corresponding classical algorithms like simulated annealing. Our results on a 496 qubit D-Wave Two quantum annealing device are compared to recently-used state-of-the-art thermal simulated annealing codes.