Two-fluid physical modeling of superconducting resonators in the ARTEMIS framework

ORAL

Abstract

In this work, we implement a new London equation module for superconductivity in the GPU-enabled ARTEMIS framework, and couple it to a finite-difference time-domain solver for Maxwell's equations. We apply this two-fluid approach to model a superconducting coplanar waveguide (CPW) resonator. We validate our implementation by verifying that the theoretical skin depth and reflection coefficients can be obtained for several superconductive materials, with different London penetration depths, over a range of frequencies. Our convergence studies show that the algorithm is second-order accurate in both space and time, except at superconducting interfaces where the approach is spatially first-order. In our CPW simulations, we leverage the GPU scalability of our code to compare the two-fluid model to more traditional approaches that approximate superconducting behavior and demonstrate that superconducting physics can show comparable performance to the assumption of quasi-infinite conductivity as measured by the Q-factor.

* This work was supported by Laboratory Directed Research and Development (LDRD) funding from Berkeley Lab, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This work was supported in part by the U.S. Department of Energy Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Visiting Faculty Program (VFP).

Publication: R. Jambunathan, Z. Yao, R. Lombardini, A. Rodriguez, and A. Nonaka, Two-Fluid Physical Modeling of Superconducting Resonators in the ARTEMIS Framework, Computer Physics Communications, 291, 2023.
Z. Yao, R. Jambunathan, Y. Zeng, and A. Nonaka, A Massively Parallel Time-Domain Coupled Electrodynamics-Micromagnetics Solver, International Journal of High Performance Computing Applications, 10943420211057906, 2021.

Presenters

  • Andy J Nonaka

    Lawrence Berkeley National Laboratory

Authors

  • Andy J Nonaka

    Lawrence Berkeley National Laboratory

  • Zhi (Jackie) Yao

    Lawrence Berkeley National Laboratory

  • Revathi Jambunathan

    Lawrence Berkeley National Laboratory

  • Richard Lombardini

    St. Mary's University

  • Aaron Rodriguez

    St. Mary's University