Performance of Qutrit QAOA Algorithm with Fixed Parameters under Noise

In the era of noisy intermediate-scale quantum (NISQ) devices, a key research challenge is to assess how various error sources affect quantum algorithms, thereby defining the limits of their practical use. This work investigates the scalability of the qutrit version of the QAOA algorithm with fixed parameters, as well as its robustness to errors in the angles of two-qutrit rotations. Numerical experiments show that angular errors of less than 0.02 radians have an insignificant impact on the algorithm’s performance for the depth p = 2. The work also analyzes the “depth–accuracy” trade-off between the algorithm’s speedup due to an increase in its depth (number of layers) and its slowdown due to the corresponding increase in the influence of quantum noise.