Utilizing discrete variable representations for decoherence-accurate numerical simulation of superconducting circuits

Given the prevalence of superconducting platforms for uses in quantum computing and quantum sensing, the simulation of quantum superconducting circuits has become increasingly important for identifying system characteristics and modeling their relevant dynamics. Various numerical tools and software packages have been developed with this purpose in mind, typically utilizing the harmonic oscillator basis or the charge basis to represent a Hamiltonian. In this work, we instead consider the use of discrete variable representations (DVRs) to model superconducting circuits. In particular, we use `sinc DVRs' of both charge number and phase to approximate the eigenenergies of several prototypical examples, exploring their use and effectiveness in the numerical analysis of superconducting circuits. We find that not only are these DVRs capable of achieving decoherence-accurate simulation, i.e., accuracy at the resolution of experiments subject to decay, decoherence, and dephasing, they also demonstrate improvements in efficiency with smaller basis sizes and better convergence over standard approaches, showing that DVRs are an advantageous alternative for representing superconducting circuits.