  We investigate a quantum perceptron implemented on a quantum circuit using a
repeat until method. We evaluate this from the perspective of capacity, one of
the performance evaluation measures for perceptions. We assess a Gardner
volume, defined as a volume of coefficients of the perceptron that can
correctly classify given training examples using the replica method. The model
is defined on the quantum circuit. Nevertheless, it is straightforward to
assess the capacity using the replica method, which is a standard method in
classical statistical mechanics. The reason why we can solve our model by the
replica method is the repeat until method, in which we focus on the output of
the measurements of the quantum circuit. We find that the capacity of a quantum
perceptron is larger than that of a classical perceptron since the quantum one
is simple but effectively falls into a highly nonlinear form of the activation
function.
