MilestoneTheory & algorithmsConfirmed
MIT physicists propose QAOA, a quantum algorithm for approximate optimization
Nov 14, 2014
Edward Farhi, Jeffrey Goldstone and Sam Gutmann of MIT post the quantum approximate optimization algorithm, which looks for good approximate answers to combinatorial optimization problems, such as splitting a network into two groups that cut as many links as possible (MaxCut).
Why it matters
Optimization is a hoped-for use of quantum computers. QAOA lets users trade circuit depth for answer quality, which suits small early machines that cannot run long programs.
Edward Farhi · Jeffrey Goldstone · Sam Gutmann · MIT
Related
Source
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arXiv (Farhi, Goldstone and Gutmann)
A Quantum Approximate Optimization Algorithm
“We introduce a quantum algorithm that produces approximate solutions for combinatorial optimization problems. The algorithm depends on a positive integer p and the quality of the approximation improves as p is increased.”
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