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Quantum neural networks to simulate many-body quantum systems
- Source :
- Phys. Rev. B 98, 184304 (2018)
- Publication Year :
- 2018
-
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.<br />Comment: 6 pages, 4 figures
- Subjects :
- Quantum Physics
Subjects
Details
- Database :
- arXiv
- Journal :
- Phys. Rev. B 98, 184304 (2018)
- Publication Type :
- Report
- Accession number :
- edsarx.1805.05462
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1103/PhysRevB.98.184304