Machine Learning Phase Transitions with a Quantum Processor

@article{Uvarov2019MachineLP,
  title={Machine Learning Phase Transitions with a Quantum Processor},
  author={A. Uvarov and A. Kardashin and J. Biamonte},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.10155}
}
  • A. Uvarov, A. Kardashin, J. Biamonte
  • Published 2019
  • Physics, Computer Science
  • ArXiv
  • Machine learning has emerged as a promising approach to unveil properties of many-body systems. Recently proposed as a tool to classify phases of matter, the approach relies on classical simulation methods---such as Monte Carlo---which are known to experience an exponential slowdown when simulating certain quantum systems. To overcome this slowdown while still leveraging machine learning, we propose a variational quantum algorithm which merges quantum simulation and quantum machine learning to… CONTINUE READING
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