Optimizing frequency allocation for fixed-frequency superconducting quantum processors

Fixed-frequency superconducting quantum processors are one of the most mature computing architectures with high-coherence qubits and simple controls. However, high-fidelity multi-qubit gates pose tight requirements on individual qubit frequencies in these , constraints difficult to satisfy when constructing larger due large dispersion fabrication Josephson junctions. In this article, we propose a mixed-integer-programming-based optimization approach that determines maximize yield processors. We study traditional qutrit (three-level) cross-resonance interaction compare differential AC-Stark shift based entanglement show our greatly improves also increases scalability devices. Our is general can be adapted problems where must avoid specific frequency collisions.