We apply our recent Quantum Approximate Optimization Algorithm to the combinatorial problem of bounded occurrence Max E3LIN2. The input is a set of linear equations each of which contains exactly three boolean variables and each equation says that the sum of the variables mod 2 is 0 or is 1. Every variable is in no more than D equations. A random string will satisfy 1/2 of the equations. We show that the level one QAOA will efficiently produce a string that satisfies (21+101D1/2lnD1) times the number of equations. A recent classical algorithm achieved (21+D1/2constant). We also show that in the typical case the quantum computer will output a string that satisfies (21+23eD1/21) times the number of equations.
@article{arxiv.1412.6062,
title = {A Quantum Approximate Optimization Algorithm Applied to a Bounded Occurrence Constraint Problem},
author = {Edward Farhi and Jeffrey Goldstone and Sam Gutmann},
journal= {arXiv preprint arXiv:1412.6062},
year = {2015}
}
Comments
This version contains a tighter analysis that leads to stronger results on the performance of the quantum algorithm