Scqubits: a Python package for superconducting qubits

TL;DR

scqubits is an open-source Python package that simplifies the simulation, analysis, and visualization of superconducting qubits and circuits, supporting complex systems and coherence time estimation.

Contribution

It introduces a comprehensive, user-friendly Python library for modeling superconducting qubits, including spectral analysis, visualization, noise modeling, and integration with QuTiP.

Findings

Supports multiple qubit types and coupled systems

Provides tools for estimating coherence times under noise

Includes GUI widgets for easier exploration

Abstract

$\textbf{scqubits}$ is an open-source Python package for simulating and analyzing superconducting circuits. It provides convenient routines to obtain energy spectra of common superconducting qubits, such as the transmon, fluxonium, flux, cos(2$\phi$) and the 0-$\pi$ qubit. $\textbf{scqubits}$ also features a number of options for visualizing the computed spectral data, including plots of energy levels as a function of external parameters, display of matrix elements of various operators as well as means to easily plot qubit wavefunctions. Many of these tools are not limited to single qubits, but extend to composite Hilbert spaces consisting of coupled superconducting qubits and harmonic (or weakly anharmonic) modes. The library provides an extensive suite of methods for estimating qubit coherence times due to a variety of commonly considered noise channels. While all functionality of $\textbf{scqubits}$ can be accessed programatically, the package also implements GUI-like widgets that, with a few clicks can help users both create relevant Python objects, as well as explore their properties through various plots. When applicable, the library harnesses the computing power of multiple cores via multiprocessing. $\textbf{scqubits}$ further exposes a direct interface to the Quantum Toolbox in Python (QuTiP) package, allowing the user to efficiently leverage QuTiP's proven capabilities for simulating time evolution.