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Tensor-network representation of excitations in Josephson junction arrays

2025/10/09 by Emilio Rui, Joachim Cohen, Rui, Emilio +3
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Physical sciences #Mesoscale and Nanoscale Physics (cond-mat.mes-hall) #Physics of Superconductivity and Magnetism #Quantum Physics (quant-ph) #Quantum and electron transport phenomena

paper · pdf · doi:10.48550/arxiv.2510.08680

openalex publication_date 2025/10/09 · openalex created_date 2025/10/17 · openalex updated_date 2026/07/28

Abstract

We present a nonperturbative tensor-network approach to the excitation spectra of superconducting circuits based on Josephson junction arrays. These arrays provide the large lumped inductances required for qubit designs, yet their intrinsically many-body nature is typically reduced to effective single-mode descriptions. Perturbative treatments attempt to include the collective array modes neglected in these approximations, but a fully nonperturbative analysis is challenging due to the many-body structure and the collective character of these modes. We overcome this difficulty using the DMRG-X algorithm, which extends tensor-network methods to excited states. Our key advance is a construction of trial states from the linearized mode structure, enabling direct computation of excitations, even in degenerate manifolds, which was previously inaccessible. Our results reveal significant deviations from, and allow us to improve upon, previous perturbative treatments in the regime of low array junction impedance.

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