Multiobjective Optimization for Robust Holonomic Quantum Gates

The practical implementation of high-fidelity quantum gates faces significant challenges in simultaneously mitigating multiple operational errors arising from distinct physical mechanisms. These errors often span orders of magnitude in severity, and their respective suppression strategies may inherently conflict. In this work, we develop a universal multiobjective optimization framework for quantum gate design by integrating Pareto optimal solutions with an entropy-weight method. Using Rydberg-based nonadiabatic holonomic quantum gates (affected by amplitude errors, detuning errors, and Rydberg decoherence) as a testbed, we theoretically demonstrate the superiority of our algorithm. The optimized gates exhibit enhanced fidelity and robustness compared to those derived from one-objective optimization strategies. Furthermore, this framework is readily adaptable to other quantum gate protocols and provides a robust foundation for advancing fault-tolerant quantum computing.