331 citations · 1.5k across the 33 of their papers we have counts for
14 papers · 1 filter
Tutorial: Calibration refinement in quantum annealing
Kevin Chern, Kelly Boothby, Jack Raymond +2
Quantum annealing has emerged as a powerful platform for simulating and optimizing classical and quantum Ising models. Quantum annealers, like other quantum and/or analog computing…
Quantum critical dynamics in a 5000-qubit programmable spin glass
Andrew D. King, Jack Raymond, Trevor Lanting +24
Experiments on disordered alloys suggest that spin glasses can be brought into low-energy states faster by annealing quantum fluctuations than by conventional thermal annealing. Du…
Coherent quantum annealing in a programmable 2000-qubit Ising chain
Andrew D. King, Sei Suzuki, Jack Raymond +21
Quantum simulation has emerged as a valuable arena for demonstrating and understanding the capabilities of near-term quantum computers. Quantum annealing has been used successfully…
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…
Essentially exact numerical modelling of flux qubit chains subject to charge and flux noise
Matthew R. C. Fitzpatrick, Jack Raymond, Malcolm P. Kennett
We present an essentially exact numerical method for modelling flux qubit chains subject to charge and flux noise. We define an essentially exact method as one that introduces erro…
Architectural considerations in the design of a third-generation superconducting quantum annealing processor
Kelly Boothby, Colin Enderud, Trevor Lanting +46
Early generations of superconducting quantum annealing processors have provided a valuable platform for studying the performance of a scalable quantum computing technology. These s…
Quantum annealing simulation of out-of-equilibrium magnetization in a spin-chain compound
Andrew D. King, Cristian D. Batista, Jack Raymond +5
Geometrically frustrated spin-chain compounds such as Ca3Co2O6 exhibit extremely slow relaxation under a changing magnetic field. Consequently, both low-temperature laboratory expe…
Improving performance of logical qubits by parameter tuning and topology compensation
Jack Raymond, Ndiamé Ndiaye, Gautam Rayaprolu +1
Optimization or sampling of arbitrary pairwise Ising models, in a quantum annealing protocol of constrained interaction topology, can be enabled by a minor-embedding procedure. The…
Simulating the Shastry-Sutherland Ising Model using Quantum Annealing
Paul Kairys, Andrew D. King, Isil Ozfidan +4
Frustration represents an essential feature in the behavior of magnetic materials when constraints on the microscopic Hamiltonian cannot be satisfied simultaneously. This gives ris…
Next-Generation Topology of D-Wave Quantum Processors
Kelly Boothby, Paul Bunyk, Jack Raymond +1
This paper presents an overview of the topology of D-Wave's next-generation quantum processors. It provides examples of minor embeddings and discusses performance of embedding algo…
Scaling advantage in quantum simulation of geometrically frustrated magnets
Andrew D. King, Jack Raymond, Trevor Lanting +51
The promise of quantum computing lies in harnessing programmable quantum devices for practical applications such as efficient simulation of quantum materials and condensed matter s…
Observation of topological phenomena in a programmable lattice of 1,800 qubits
Andrew D. King, Juan Carrasquilla, Isil Ozfidan +20
The celebrated work of Berezinskii, Kosterlitz and Thouless in the 1970s revealed exotic phases of matter governed by topological properties of low-dimensional materials such as th…
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…
Global warming: Temperature estimation in annealers
Jack Raymond, Sheir Yarkoni, Evgeny Andriyash
Sampling from a Boltzmann distribution is NP-hard and so requires heuristic approaches. Quantum annealing is one promising candidate. The failure of annealing dynamics to equilibra…