CB statuses in the path $P_i$, is consistent with the readouts $l_i$, and $g_i=1$ when the prediction and the readout are in disagreement. In other words, $g_i = \textsc{xor}(f_i,l_i)$

$H_{\text{numFaults}}$ is proportional to the number of faults (whenever $x_i = 0$ or $y_i = 0$) in the electrical network, $$\label{eq:Hfaults}
H_{\text{numFaults}} = \lambda^{\text{CB}}_{\text{faults}} \sum_{i=1}^{n_{\text{CB}}} (1-x_i)+ \lambda^{\text{sensor}}_{\text{faults}} \sum_{i=1}^{n_{\text{sensor}}} (1-y_i),$$ and when combined with $H_{\text{consist}}$, as written in Eq. \[eq:Hproblem\], defines the problem energy function to be minimized by favoring the minimal set of faulty components that are simultaneously consistent with the observations measured in the outermost sensors.

There is an important difference between the implementation of the search with a quantum algorithm when compared to an implementation with a conventional classical computer. Doing <span style="font-variant:small-caps;">if</span> loops and checking whether or not a certain solution is consistent with the observations is an easy task on a conventional computer, since one can interrupt the process at any time to accept or to reject a solution candidate to the problem. In a quantum device, this checking procedure of measuring whether the state is in accordance with the observations, can only be done once, which happens at the end of the quantum annealing schedule, since 