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Investigation of the Performance of Different QAOA Variants Under the Influence of Realistic Noise

Quantum computers have the potential to solve certain problems much more efficiently in the future than would be possible with conventional computers. In particular, the Quantum Approximate Optimization Algorithm (QAOA), including its various variants, has produced promising results on quantum simulators for a variety of optimization problems. In practice, however, noise and other errors are characteristic of computation on real quantum computers. This work addresses the question of how noise affects the performance of different QAOA variants. In particular, we will investigate which QAOA variants are particularly resistant to noise and which amounts of noise can be tolerated. These questions will be answered with the help of realistic numerical simulations.