Abstract
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(2ϕ) and the 0-π qubit. 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 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. 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.
Highlights
The computation of energy spectra, eigenstates, and matrix elements of relevant operators is a key prerequisite for the design and fabrication of superconducting qubits, as well as for the quantitative analysis of experimental data collected in state-ofthe-art experiments
The scqubits package provides a user-friendly, object-oriented Python library of the most common superconducting qubits. It facilitates automatic construction of circuit Hamiltonians in an appropriate basis, provides high-level routines for finding eigenenergies, eigenstates, and matrix elements, and allows the user to quickly visualize these quantities as a function of external parameters
Matrix elements of qubit operators play an important role in determining coupling strengths between a qubit and another quantum system
Summary
Superconducting qubits [7, 10, 17, 27] have secured the rank of one of the most promising and widely researched hardware architectures for quantum information processing All devices in this category are relatively simple circuits, and display genuine quantum properties such as discrete energy spectra and quantum-coherent time evolution. The scqubits package provides a user-friendly, object-oriented Python library of the most common superconducting qubits. It facilitates automatic construction of circuit Hamiltonians in an appropriate basis, provides high-level routines for finding eigenenergies, eigenstates, and matrix elements, and allows the user to quickly visualize these quantities as a function of external parameters. While typical values are suggested in each widget, convergence with respect to this cutoff (and similar cutoffs in other qubit classes) must be established by the user (see 2.1.1 below for a more detailed discussion)
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