SAMOP 2023 – wissenschaftliches Programm
Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
QI: Fachverband Quanteninformation
QI 30: Quantum Algorithms
QI 30.2: Vortrag
Donnerstag, 9. März 2023, 15:00–15:15, B305
Performance of Portfolio Optimization with QAOA — •Vanessa Dehn and Thomas Wellens — Fraunhofer Institut für Angewandte Festkörperphysik IAF, Freiburg, Deutschland
The quantum approximate optimization algorithm (QAOA) is a promising candidate to solve the portfolio optimization problem more efficiently than classical computers in case of a large number of assets. For a given list of assets, the problem is formulated as a quadratic binary optimization problem and studied using different versions of QAOA (different mixers). To solve the problem with good performance, we discuss technical aspects such as providing a good choice of the penalty factor in case of the standard version of QAOA and deducing suitable initial circuit parameters as starting point for the classical optimizer [1]. Furthermore, we investigate the warm-start version of QAOA and evaluate to what extent the improved performance of WS-QAOA is due to quantum effects.
[1] S. Brandhofer, D. Braun, V. Dehn, G. Hellstern, M. Hüls, Y. Ji, I. Polian, A. Singh Bhatia and T. Wellens, arXiv:2207.10555