How to Approximate any Objective Function via Quadratic Unconstrained Binary Optimization

Gabor, Thomas; Rosenfeld, Marian Lingsch; Linnhoff-Popien, Claudia und Feld, Sebastian (2022): How to Approximate any Objective Function via Quadratic Unconstrained Binary Optimization. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Honolulu, HI, USA, 15-18 March 2022. In: 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), S. 1249-1257

Abstract

Quadratic unconstrained binary optimization (QUBO) has become the standard format for optimization using quantum computers, i.e., for both the quantum approximate optimization algorithm (QAOA) and quantum annealing (QA). We present a toolkit of methods to transform almost arbitrary problems to QUBO by (i) approximating them as a polynomial and then (ii) translating any polynomial to QUBO. We showcase the usage of our approaches on two example problems (ratio cut and logistic regression).

• Dokumententyp: Konferenzbeitrag (Paper)
• Fakultät: Mathematik, Informatik und Statistik > Informatik
• Themengebiete: 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik
• Sprache: Englisch