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Technology based on memristors, resistors with memory whose resistance depends on the history of the crossing charges, has lately enhanced the classical paradigm of computation with neuromorphic architectures.
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Traversa, F. L., Ramella, C., Bonani, F. & di Ventra, M. Memcomputing NP-complete problems in polynomial time using polynomial resources and collective states. Sci. Adv
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Di Ventra, M. & Pershin, Y. V. On the physical properties of memristive, memcapacitive and meminductive systems. Nanotechnology
2013
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2013
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Felicetti, S. et al. Dynamical Casimir effect entangles artificial atoms. Phys. Rev. Lett
2014
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Peotta, S. & di Ventra, M. Superconducting memristors. Phys. Rev. Applied
2014
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Schlosshauer, M. The quantum-to-classical transition and decoherence. arXiv:1404.2635 (2014)
2014
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Traversa, F. L. & di Ventra, M. Universal memcomputing machines. IEEE Trans. Neur. Networks and Learn. Sys
2015
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2015
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2015
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2015
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Simonite T., IBM making plans to commercialize its brain-inspired chip
2015
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2016
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Salmilehto, J., Deppe, F., di Ventra, M., Sanz, M. & Solano, E. Quantum memristors with superconducting circuits. ArXiv: 1603.04487 (2016)
2016
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