Optimization algorithms, machine learning and artificial intelligence in quantum computation
The latest years have seen great advancements in developing quantum computers, yet scientists and engineers will have to resort to NISQ (noisy intermediate-scale quantum) solutions in the near future. This requires quantum protocols and algorithms optimized for these architectures. We will design so-called variational quantum algorithms for quantum-gate-based architectures, with which we will solve optimisation and machine learning tasks. For adiabatic quantum architectures, we transform certain, chiefly combinatorial, optimisation tasks into quadratic unconstrained binary optimisation (QUBO) problems.