Using Universal Frame Randomization and Randomized Compilation to Mitigate Errors in Quantum Optimization

Error mitigation is essential for near-term quantum devices, and two promising techniques are universal frame randomization and Randomized Compilation. These methods insert random twirling gates into a circuit to reduce errors while preserving unitarity and depth. We apply universal frame randomization and Randomized Compilation to the quantum approximate optimization algorithm (QAOA) with p=1 on a superconducting quantum circuit system, demonstrating its potential to improve energy calculations. Specifically, we investigate the use of QAOA to calculate the lowest energy state of a frustrated Ising ring system and compare the results of randomized circuits generated using both techniques. Our results show that both methods can mitigate errors, with expected extremal energy values of 5.25±0.145 and 4.08±0.36, for Randomized Compilation and universal frame randomization respectively, compared to 2.63±0.068 without randomization and 5.676±0.006 with a noiseless simulator.