We introduce an efficient tensor network toolbox to compute the low-energy excitations of large-scale superconducting quantum circuits up to a desired accuracy. We benchmark this algorithm on the fluxonium qubit, a superconducting quantum circuit based on a Josephson junction array with over a hundred junctions. As an example of the possibilities offered by this numerical tool, we compute the pure-dephasing coherence time of the fluxonium qubit due to charge noise and coherent quantum phase slips, taking into account the array degrees of freedom corresponding to a Hilbert space as large as15180. Our algorithm is applicable to the wide variety of circuit-QED systems and may be a useful tool for scaling up superconducting-qubit technologies.
@article{arxiv.1912.01018,
title = {Efficient modeling of superconducting quantum circuits with tensor networks},
author = {Agustin Di Paolo and Thomas E. Baker and Alexandre Foley and David Sénéchal and Alexandre Blais},
journal= {arXiv preprint arXiv:1912.01018},
year = {2021}
}