  Humans routinely solve problems of immense computational complexity by
intuitively forming simple, low-dimensional heuristic strategies. Citizen
science exploits this ability by presenting scientific research problems to
non-experts. Gamification is an effective tool for attracting citizen
scientists to provide solutions to research problems. While citizen science
games Foldit, EteRNA and EyeWire have been used successfully to study protein
and RNA folding and neuron mapping, so far gamification has not been applied to
problems in quantum physics. Does the fact that everyday experiences are based
on classical physics hinder the use of non-expert citizen scientists in the
realm of quantum mechanics? Here we report on Quantum Moves, an online platform
gamifying optimization problems in quantum physics. We show that human players
are able to find solutions to difficult problems associated with the task of
quantum computing. Players succeed where purely numerical optimization fails,
and analyses of their solutions provide insights into the problem of
optimization of a more profound and general nature. Based on player strategies,
we have thus developed a new, few-parameter heuristic optimization method which
efficiently outperforms the most prominent established numerical methods. The
numerical complexity associated with time-optimal solutions increases for
shorter process durations. To better understand this, we have made a
low-dimensional rendering of the optimization landscape. These studies show why
traditional optimization methods fail near the quantum speed limit, and they
bring promise that combined analyses of optimization landscapes and heuristic
solution strategies may benefit wider classes of optimization problems in
quantum physics and beyond.
