Speaker: Luca Asproni (Data Reply)
The Number Partitioning Problem (NPP) is a NP-Hard optimization model that represents one of the most complex scenarios in terms of qubits connectivity. It requires fully connectivity between qubits and, as the input problem size grows, it poses some great challenges to state-of-the-art quantum annealers. In this work we report our findings as in Ref. 1 regarding the capabilities of the D-Wave Quantum Annealer employed to explore the solution space of a number of instances of the NPP, with increasing difficulty, via a hybrid quantum- classical procedure. We exploit the features that allow to schedule the annealing time and pauses. Being able to tune the parameters of the annealing cycle, we find the optimal solution of all the instances analysed. We record statistics of the results, reporting the frequency with which the system ends up in the ground state and how far the solution is from it, in terms of the NPP objective function. Finally, we study the solution quality over multiple lengths of the annealing pause.