Quantum-inspired optimization leverages principles from quantum mechanics to enhance classical algorithms, offering novel approaches to solve complex binary optimization problems potentially more efficiently. Binary optimization has a wide range of applications including logistics, finance, machine learning or pharmacy.

In this talk we will give an overview over classical as well as quantum and quantum-inspired algorithms to heuristically solve binary optimization problems including simulated annealing, parallel tempering, quantum annealing and simulated quantum annealing. We will compare these algorithms and discuss their respective advantages and disadvantages.

Topics of the talk:

Introduction to quadratic binary optimization
Classical algorithms
Quantum and quantum-inspired algorithms

Weitere Infos und Anmeldung