Preprocessing Method for Microwave Resonator Fitting

We present a preprocessing method for S21 data from superconducting microwave resonators. In the field of quantum computing, it is becoming increasingly necessary to charactarize loss in superconducting circuits to a higher degree of accuracy. The goal of the code implemented is to provide a rigorous standard for charactarizing this loss. The method is implemented in python where the Diameter Correction Method, Inverse S21 method and Closest Pole and Zero method are all used in conjunction with the preprocessing. Accuracy of the preprocessing method is tested by comparing results from computer simulated resonator data from circuit elements to calculated values from the circuit elements of the simulated data. The preprocessing method entails a removal of the S21 data background by linear fit of the end points for both magnitude and phase, as well as the option to remove background from a user background file (a dataset of the same format without resonator behavior to establish a baseline). Testing the preprocessing method across varying parameters of circuit elements allows us to view correlation between preprocessing and error in determination of parameters.