80 citations · 239 across the 6 of their papers we have counts for
8 papers
Milestones on the Quantum Utility Highway
Catherine C. McGeoch, Pau Farre
We introduce quantum utility, a new approach to evaluating quantum performance that aims to capture the user experience by including overhead costs associated with the quantum comp…
Optimization Applications as Quantum Performance Benchmarks
Thomas Lubinski, Carleton Coffrin, Catherine McGeoch +3
Combinatorial optimization is anticipated to be one of the primary use cases for quantum computation in the coming years. The Quantum Approximate Optimization Algorithm (QAOA) and…
Hybrid quantum annealing for larger-than-QPU lattice-structured problems
Jack Raymond, Radomir Stevanovic, William Bernoudy +5
Quantum processing units (QPUs) executing annealing algorithms have shown promise in optimization and simulation applications. Hybrid algorithms are a natural bridge to additional…
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 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 analy…
A cross-disciplinary introduction to quantum annealing-based algorithms
Salvador E. Venegas-Andraca, William Cruz-Santos, Catherine McGeoch +1
A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in q…
Quantum Annealing amid Local Ruggedness and Global Frustration
James King, Sheir Yarkoni, Jack Raymond +5
A recent Google study [Phys. Rev. X, 6:031015 (2016)] compared a D-Wave 2X quantum processing unit (QPU) to two classical Monte Carlo algorithms: simulated annealing (SA) and quant…
Benchmarking a quantum annealing processor with the time-to-target metric
James King, Sheir Yarkoni, Mayssam M. Nevisi +2
In the evaluation of quantum annealers, metrics based on ground state success rates have two major drawbacks. First, evaluation requires computation time for both quantum and class…
Algorithm engineering for a quantum annealing platform
Andrew D. King, Catherine C. McGeoch
Recent advances bring within reach the viability of solving combinatorial problems using a quantum annealing algorithm implemented on a purpose-built platform that exploits quantum…