Analysis of arbitrary superconducting quantum circuits accompanied by a Python package: SQcircuit

Superconducting quantum circuits are a promising hardware platform for realizing a fault-tolerant quantum computer. Accelerating progress in this field of research demands general approaches and computational tools to analyze and design more complex superconducting circuits. We develop a framework to systematically construct a superconducting quantum circuit's quantized Hamiltonian from its physical description. As is often the case with quantum descriptions of multi-coordinate systems, the complexity rises rapidly with the number of variables. Therefore, we introduce a set of coordinate transformations with which we can find bases to diagonalize the Hamiltonian efficiently. Furthermore, we broaden our framework's scope to calculate the circuit's key properties required for optimizing and discovering novel qubits. We implement the methods described in this work in an open-source Python package SQcircuit. In this presentation, we introduce the audience to the technical implementation of SQcircuit and its functionalities with a series of examples. Moreover, we present our preliminary results for SQcircuit development to address the large-scale circuits and our roadmap to use machine learning techniques to discover novel quantum hardware.