  One of the main challenges in building a quantum processor is to characterize
the environmental noise. Noise characterization can be achieved by exploiting
different techniques, such as randomization where several sequences of random
quantum gates are applied to the qubit under test to derive statistical
characteristics about the affecting noises. A scalable and robust algorithm
able to benchmark the full set of Clifford gates using randomization techniques
is called randomized benchmarking. In this study, we simulated randomized
benchmarking protocols in a semiconducting all-electrical three-electron
double-quantum dot qubit, i.e. hybrid qubit, under different error models, that
include quasi-static Gaussian and the more realistic 1/f noise model, for the
input controls. The average error of specific quantum computational gates is
extracted through interleaved randomized benchmarking obtained including
Clifford gates between the gate of interest. It provides an estimate of the
fidelity as well as theoretical bounds for the average error of the gate under
test.

Quantum Physics