# Automated analysis of single-tone spectroscopic data for cQED systems

## TL;DR

This paper introduces an automated, robust, and fast tool for analyzing single-tone spectroscopy data in cQED systems, enabling precise calibration of quantum devices through maximum likelihood estimation.

## Contribution

The authors developed an open-source Python tool that automates the analysis of STS data for cQED systems, improving calibration efficiency and accuracy.

## Key findings

- The tool accurately extracts physical parameters from noisy STS data.
- It significantly reduces calibration time for transmon qubits.
- The approach is validated on real cQED devices.

## Abstract

Physical systems for quantum computation require calibration of the control parameters based on their physical characteristics by performing a chain of experiments that gather most precise information about the given device. It follows that there is a need for automated data acquisition and interpretation. In this work, we have developed a tool that allows for automatic analysis of single-tone spectroscopy (STS) results for a single cell consisting of qubit and resonator in the circuit quantum electrodynamics (cQED) architecture. Using analytic approaches and maximum likelihood estimation, our algorithm is capable of finding all relevant physical characteristics of the cell by using only the measured STS data. The described approach is fast and robust to noise, and its open-source Python implementation can readily be used to calibrate transmon qubits coupled to notch-port resonators.