Crowdsourcing human common sense for quantum control

Citizen science has been applied with great success to help solve complex numerical challenges within microbiology, e.g. protein folding. Quantum physics offers similarly complex challenges, yet there is no systematic research effort exploring the potential of citizen science in this domain. We take first steps in this direction by introducing a game, Quantum Moves 2, and in three different quantum control problems compare the efficacy of various optimization methods: gradient-optimization with player-based seeds and random seeds, and gradient-free with random seeds. Although approximately optimal results can be obtained within reasonable computational resources, the considered problems fall into distinct degrees of complexity. Players can apply the gradient-based algorithm to their seeds and we find that these results perform roughly on par with the best of the standard optimization methods. This highlights the future potential for crowdsourcing the solution of quantum research problems. Further, cluster-optimized player seeds was the only method to yield roughly optimal performance throughout all problems. We are aware that comparisons with random seeding constitutes the lowest bar of comparison with the plethora of possible optimization approaches and our work should therefore only be taken as a necessary first demonstration of the potential for further exploration. Additionally, since the three challenges are much simpler than the problem of folding proteins, they also lend themselves to different research questions. Where protein folding focuses on the results of a small subset of players achieving near expert status, we explore bulk behavior of all players. The relative success of the player seeds indicates, in our view, the potential value of studying the crowdsourcing of common sense, the innate responses of all players to the interface, as inspiration for expert optimization.