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We extend the ability of unitary quantum circuits by interfacing it with classical autoregressive neural networks.
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Albrecht Huber, “Variational principles in quantum statistical mechanics,” in Mathematical Methods in Solid State and Superfluid Theory (Springer, 1968) pp. 364–392
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Barbara M. Terhal and David P. DiVincenzo, “Problem of equilibration and the computation of correlation functions on a quantum computer,” Phys. Rev. A 61
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Matthias Troyer and Uwe Jens Wiese, “Computational complexity and fundamental limitations to fermionic quantum Monte Carlo simulations,” Phys. Rev. Lett. 94
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Abhinav Kandala, Antonio Mezzacapo, Kristan Temme, Maika Takita, Markus Brink, Jerry M Chow, and Jay M Gambetta, “Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets,” Nature 549
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2009
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2011
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Michael A. Nielsen and Isaac L. Chuang, Quantum Computation and Quantum Information: 10th Anniversary Edition , 10th ed. (Cambridge University Press, New York, USA, 2011)
2011
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K. Van Houcke, F. Werner, E. Kozik, N. Prokof’ev, B. Svistunov, M. J.H. Ku, A. T. Sommer, L. W. Cheuk, A. Schirotzek, and M. W. Zwierlein, “Feynman diagrams versus Fermi-gas Feynman emulator,” Nat. Phys. 8
2012
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2012
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Diederik P Kingma and Max Welling, “Auto-Encoding Variational Bayes,” (2013) , arXiv:1312.6114
2013
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2014
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2014
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2018
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2018
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Lei Wang, “Generative models for physicists,” http://wangleiphy.github.io/lectures/PILtutorial.pdf (2018)
2018
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K Mitarai, M Negoro, M Kitagawa, and K Fujii, “Quantum circuit learning,” Phys. Rev. A 98
2018
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