Lurking in the background of the quest for true quantum supremacy hangs an awkward possibility – hyper-fast number crunching tasks based on quantum trickery might just be a load of hype.

Now, a pair of physicists from École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland and Columbia University in the US have come up with a better way to judge the potential of near-term quantum devices – by simulating the quantum mechanics they rely upon on more traditional hardware.

Their study made use of a neural network developed by EPFL’s Giuseppe Carleo and his colleague Matthias Troyer back in 2,016 using machine learning to come up with an approximation of a quantum system tasked with running a specific process.