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arXiv · 1805.05462

Quantum neural networks to simulate many-body quantum systems

Bartłomiej Gardas·Marek M. Rams·Jacek Dziarmaga
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Abstract

We conduct experimental simulations of many body quantum systems using a \emph{hybrid} classical-quantum algorithm. In our setup, the wave function of the transverse field quantum Ising model is represented by a restricted Boltzmann machine. This neural network is then trained using variational Monte Carlo assisted by a D-Wave quantum sampler to find the ground state energy. Our results clearly demonstrate that already the first generation of quantum computers can be harnessed to tackle non-trivial problems concerning physics of many body quantum systems.

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Bartłomiej Gardas, Marek M. Rams, Jacek Dziarmaga. 2018-05-14. Quantum neural networks to simulate many-body quantum systems. https://doi.org/10.1103/physrevb.98.184304

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