Overview of the Quantum Approximate Optimization Algorithm (QAOA) variants

Talk will be given by Anna Zając from AGH University.

Abstract
In this talk, we will present an evaluation of three variants of the Quantum Approximate Optimization Algorithm: the warm-started version [1], which aims to improve upon the best achievable classical solution, the recursive version [2], which proposes a variable elimination technique to solve smaller problems in every recursion step, and combination of those two variants – warm-started recursive version [1].
We will discuss how the choice of the algorithm and circuit depth impacts the quality of the solution to two kinds of problems: Maximum Cut and Workflow Scheduling, for which three different encodings will be addressed [3].
Additionally, to the experiments conducted on simulators, the results of the experiments conducted on quantum processors available through IBM Quantum will be discussed. We will also present some insights on work with larger quantum processors and the IBM Runtime platform.

References
[1] Egger, D. J., Mareček, J., & Woerner, S. (2021). Warm-starting quantum optimization. Quantum, 5, 479.
[2] Bravyi, S., Kliesch, A., Koenig, R., & Tang, E. (2020). Obstacles to variational quantum optimization from symmetry protection. Physical review letters, 125(26), 260505.
[3] Plewa, J., Sieńko, J., & Rycerz, K. (2021). Variational Algorithms for Workflow Scheduling Problem in Gate-Based Quantum Devices. Computing & Informatics, 40(4).

Bio:
Anna Zając is currently in the final stages of completing her Master of Science (M.Sc.) degree. She works as a Software Engineer, and her interests include data-intensive applications and distributed com-puting