Spiking neuromorphic chip learns entangled quantum states

The approximation of quantum states with artificial neural networks has gained a lot attention during the last years. Meanwhile, analog neuromorphic chips, inspired by structural and dynamical properties biological brain, show high energy efficiency in running neural-network architectures for profit generative applications. This encourages employing such hardware systems as platforms simulations systems. Here we report on realization prototype using latest spike-based BrainScaleS allowing us to represent few-qubit maximally entangled fidelities. Bell correlations pure mixed two-qubit are well captured hardware, demonstrating an important building block simulating spiking chips.