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

arXiv:1805.05217 · Science Advances

Experimental investigation of performance differences between coherent Ising machines and a quantum annealer

Ryan Hamerly, Takahiro Inagaki, Peter L. McMahon, Davide Venturelli, Alireza Marandi, Tatsuhiro Onodera, Edwin Ng, Carsten Langrock, Kensuke Inaba, Toshimori Honjo, Koji Enbutsu, Takeshi Umeki, Ryoichi Kasahara, Shoko Utsunomiya, Satoshi Kako, Ken-ichi Kawarabayashi, Robert L. Byer, M. M. Fejer, Hideo Mabuchi, Dirk Englund, Eleanor Rieffel, Hiroki Takesue, Y. Yamamoto

Published May 3, 2019• 333 citations
arXivHTMLPDF

Abstract

)] for fixed anneal times, both on the SK model and on 50% edge density MAX-CUT. This leads to a several orders of magnitude time-to-solution difference for instances with over 50 vertices. An optimal-annealing time analysis is also consistent with a substantial projected performance difference. The difference in performance between the sparsely connected D-Wave machine and the fully-connected CIMs provides strong experimental support for efforts to increase the connectivity of quantum annealers.

DOI
10.1126/sciadv.aau0823

Related papers

Experimental investigation of performance differences between coherent Ising machines and a quantum annealer

Ryan Hamerly, Takahiro Inagaki, Peter L. McMahon +20 more

Physical annealing systems provide heuristic approaches to solving combinatorial optimization problems. Here, we benchmark two types of annealing machines—a quantum annealer built by D-Wave Systems and measurement-feedback coherent Ising machines (CIMs) based on optical parametric oscillators—on two problem classes, the Sherrington-Kirkpatrick (SK) model and MAX-CUT. The D-Wave quantum annealer outperforms the CIMs on MAX-CUT on cubic graphs. On denser problems, however, we observe an exponential penalty for the quantum annealer [exp(–α_(DW)N^2)] relative to CIMs [exp(–α_(CIM)N)] for fixed anneal times, both on the SK model and on 50% edge density MAX-CUT. This leads to a several orders of magnitude time-to-solution difference for instances with over 50 vertices. An optimal–annealing time analysis is also consistent with a substantial projected performance difference. The difference in performance between the sparsely connected D-Wave machine and the fully-connected CIMs provides strong experimental support for efforts to increase the connectivity of quantum annealers.

•Jan 1, 2019•257 citations

Synchronously-pumped OPO coherent Ising machine: benchmarking and prospects

Ryan Hamerly, Takahiro Inagaki, Peter L. McMahon +4 more

The coherent Ising machine (CIM) is a network of optical parametric oscillators (OPOs) that solves for the ground state of Ising problems through OPO bifurcation dynamics. Here, we present experimental results comparing the performance of the CIM to quantum annealers (QAs) on two classes of NP-hard optimization problems: ground state calculation of the Sherrington-Kirkpatrick (SK) model and MAX-CUT. While the two machines perform comparably on sparsely-connected problems such as cubic MAX-CUT, on problems with dense connectivity, the QA shows an exponential performance penalty relative to CIMs. We attribute this to the embedding overhead required to map dense problems onto the sparse hardware architecture of the QA, a problem that can be overcome in photonic architectures such as the CIM.

AI and Optical Data Sciences•Feb 24, 2020•4 citations

Comment on "Scaling advantages of all-to-all connectivity in physical annealers: the Coherent Ising Machine vs D-Wave 2000Q" [arXiv:1805.05217]

Catherine C. McGeoch, William Bernoudy, James A. King

A recent paper [arXiv:1805.05217] compares performance of a D-Wave 2000Q system to two versions of the coherent Ising machine (CIM). This comment points out some flaws in the analysis, which undermine several of the conclusions drawn in the paper.

arXiv:1807.00089•Jun 29, 2018•2 citations

Performance Comparison between Coherent Ising Machines and Quantum Annealer

Hiroki Takesue, Takahiro Inagaki, Kensuke Inaba +1 more

NTT has been developing a coherent Ising machine (CIM), which efficiently finds solutions to groundstate-search problems of the Ising model using a network of optical parametric oscillators.We introduce our recent experiment that compared the computational performance of CIMs (the one developed by NTT and another developed by Stanford University) with a quantum annealer, which solves the Isingmodel problems using superconducting devices.

NTT technical review•May 1, 2021•3 citations

Quantum vs. Optical Annealing: Benchmarking the OPO Ising Machine and D-Wave

Ryan Hamerly, Takahiro Inagaki, Peter L. McMahon +9 more

We benchmark the OPO-based Coherent Ising Machine (CIM) against the D-Wave quantum annealer for Ising problems up to size N = 200. The CIM exhibits exponential speedup relative to D-Wave for Ising problems with dense connectivity.

Conference on Lasers and Electro-Optics•Jan 1, 2018•6 citations

Benchmarking coherent Ising machines and quantum annealers with MAX-CUT and SK problems

Ryan Hamerly, Takahiro Inagaki, Peter L. McMahon +10 more

Bulletin of the American Physical Society•Mar 6, 2019•0 citations
)] for fixed anneal times, both on the SK model and on 50% edge density MAX-CUT. This leads to a several orders of magnitude time-to-solution difference for instances with over 50 vertices. An optimal-annealing time analysis is also consistent with a substantial projected performance difference. The difference in performance between the sparsely connected D-Wave machine and the fully-connected CIMs provides strong experimental support for efforts to increase the connectivity of quantum annealers.
Physical annealing systems provide heuristic approaches to solving combinatorial optimization problems. Here, we benchmark two types of annealing machines—a quantum annealer built by D-Wave Systems and measurement-feedback coherent Ising machines (CIMs) based on optical parametric oscillators—on two problem classes, the Sherrington-Kirkpatrick (SK) model and MAX-CUT. The D-Wave quantum annealer outperforms the CIMs on MAX-CUT on cubic graphs. On denser problems, however, we observe an exponential penalty for the quantum annealer [exp(–α_(DW)N^2)] relative to CIMs [exp(–α_(CIM)N)] for fixed anneal times, both on the SK model and on 50% edge density MAX-CUT. This leads to a several orders of magnitude time-to-solution difference for instances with over 50 vertices. An optimal–annealing time analysis is also consistent with a substantial projected performance difference. The difference in performance between the sparsely connected D-Wave machine and the fully-connected CIMs provides strong experimental support for efforts to increase the connectivity of quantum annealers.
The coherent Ising machine (CIM) is a network of optical parametric oscillators (OPOs) that solves for the ground state of Ising problems through OPO bifurcation dynamics. Here, we present experimental results comparing the performance of the CIM to quantum annealers (QAs) on two classes of NP-hard optimization problems: ground state calculation of the Sherrington-Kirkpatrick (SK) model and MAX-CUT. While the two machines perform comparably on sparsely-connected problems such as cubic MAX-CUT, on problems with dense connectivity, the QA shows an exponential performance penalty relative to CIMs. We attribute this to the embedding overhead required to map dense problems onto the sparse hardware architecture of the QA, a problem that can be overcome in photonic architectures such as the CIM.