Statistical algorithms for superconducting q-bits parameters measurement

Statistical algorithms for measurement data processing were developed to perform automation of superconducting quantum bits experimental investigations. The first algorithm is aimed to detect the q-bit quantum state changes. The second one is aimed to obtain the efficient resonance frequency estimation for the resonator coupled to a q-bit. All the results were obtained using the statistical approach that employs random nature of measurement data to obtain the optimal estimation rules and statistical hypotheses testing. The numerical modeling was carried out. The results of numerical modeling confirmed the efficiency and expediency of the algorithms obtained.