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2018 | OriginalPaper | Chapter

A Survey of Programming Tools for D-Wave Quantum-Annealing Processors

Authors : Scott Pakin, Steven P. Reinhardt

Published in: High Performance Computing

Publisher: Springer International Publishing

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Abstract

The rapid growth in the realized performance of D-Wave Systems’ annealing-based quantum processing units (QPUs) has sparked a surge in tools development to deliver the anticipated performance to application developers. In this survey we describe the tools that are available, their goals (e.g., performance or ease of use), the programming abstractions they expose, and their use for application development. The existing tools confirm the need for interfaces at a variety of points on the continuum between complexity and simplicity in using the QPU. Most of the current tools abstract the hardware’s native topology but generally not using existing interfaces that are familiar to typical programmers. To date, only a small number of applications have been implemented for QPUs. Our survey finds that tools provide potentially great leverage to enable more applications as long as the tools expose the appropriate abstractions and deliver the anticipated performance.

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Footnotes
1
Note the possibility of confusion between this definition of unconstrained BQP and the definition of BQP as bounded-error quantum polynomial time [4], a computational complexity class. To avoid this confusion, we refer to the problem as a QUBO throughout this paper.
 
2
Chain strength is the relative strength of couplings between qubits corresponding to the same problem variable to couplings between qubits corresponding to different problem variables.
 
3
A chain is considered broken if its qubits, which correspond to the same problem variable, are assigned different values.
 
4
Section 2 mentions the difference between the Ising-model Hamiltonian and the QUBO. For consistency with the rest of this paper we use QUBO terminology here.
 
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Metadata
Title
A Survey of Programming Tools for D-Wave Quantum-Annealing Processors
Authors
Scott Pakin
Steven P. Reinhardt
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-92040-5_6