  This paper proposes a quantum circuit for computing the mean value from a
given set of quantum states. The circuit consults a Quantum Random Access
Memory to get the values of the set, and by using superposition, interference
and entanglement phenomena, it can estimate the mean value in
$\mathcal{O}(\frac{1}{\epsilon}\log{Nd})$ complexity. The proposed quantum
mean-estimator circuit has been simulated on the IBM Q Experience and the
results suggest that the proposed quantum circuit can have the potential to
enhance many mean-based machine learning algorithms.
