Quantization of Large Superconducting Circuits with Tensor Networks

We introduce a novel method for efficient quantum simulation of large superconducting circuits using matrix product states (MPS) and the density matrix renormalization group (DMRG) technique. We analyze an LC oscillator containing a chain of Josephson junctions, forming a superinductor. We obtain the lowest-lying eigenstates and energies, and calculate physical observables of interest for chain lengths in the range of 5-65 Josephson junctions. We quantify simulation convergence through comparison with exact diagonalization (when possible) and quantum state variance. Our approach reaches far beyond the resource limitations of brute-force exact diagonalization.