Shape Design Optimization for 3D Integrated Superconducting Quantum Processors

As the number of qubits increase in superconducting quantum processors, so does the complexity and the number of design variables. Optimizing the design parameters, including shape and layout, is of crucial importance to the successful engineering and operation of complex quantum processors such as 3D integrated devices. Such optimization problems may involve a large number of geometric design parameters with several optimization goals such as maximizing signal integrity, maximize qubit and interconnect density while minimizing crosstalk.

High fidelity, massively parallel computational toolkits which solve Maxwell equations and include advanced optimization algorithms are instrumental in addressing this challenge. In this talk, we will present such a toolkit that provides adjoint-based shape optimization capability with application to the design of 3D integrated superconducting quantum processors. We will present the mathematical background of the method as well as a few realistic examples.