Tensor networks for non-perturbative driven black-box quantization of superconducting circuit

We present a nonperturbative tensor-network approach to represent the Floquet Hamiltonian of quasiperiodically driven many-mode circuit quantum electrodynamics (cQED) systems.

Because of the unbounded nature of the Floquet Hamiltonian, and the associated spectral degeneracies, variational techniques such as DMRG struggle to compute the Floquet spectrum. We show how the DMRG-X algorithm, which relies on targeting a suitable trial state, can overcome these limitations and enable the computation of relevant quantities such as the dressed mode frequencies and nonlinearities. This method enables a scalable framework for analyzing many-body superconducting circuits with local interactions and drives, as typically used in quantum information processing.