Algorithm engineering for a quantum annealing platform
arXiv:1410.2628
Abstract
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 properties. However, the question of how to tune the algorithm for most effective use in this framework is not well understood. In this paper we describe some operational parameters that drive performance, discuss approaches for mitigating sources of error, and present experimental results from a D-Wave Two quantum annealing processor.
16 pages. V2: minor edits
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- A Hybrid Quantum-Classical Paradigm to Mitigate Embedding Costs in Quantum Annealing---Abridged Version
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- Mapping NP-Hard Problems to Restricted Adiabatic Quantum Architectures
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- Adiabatic Quantum Graph Matching with Permutation Matrix Constraints
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- Quantum Advantage for All