Sampling scheme for neuromorphic simulation of entangled quantum systems

Understand

Due to the complexity of the space of quantum many-body states the computation of expectation values by statistical sampling is, in general, a hard task.

• Neural network representations of such quantum states which can be physically implemented by neuromorphic hardware could enable efficient sampling.
• A scheme is proposed which leverages this capability to speed up sampling from so-called neural quantum states encoded by a restricted Boltzmann machine.
• Due to the complex network parameters a direct hardware implementation is not feasible.