  This article describes an improved brute-force solving strategy for Quadratic
Unconstrained Binary Optimization (QUBO) problems that is faster than naive
approaches and easily parallelizable. It exploits the Gray code ordering of
natural numbers to allow for a more efficient evaluation of the QUBO objective
function. The implementation in Python is discussed in detail, and an
additional C implementation is provided.
