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Large-scale quantum devices provide insights beyond the reach of classical simulations.
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2019
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2019
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2017
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2017
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2018
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2018
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D Zhu, S Johri, NM Linke, KA Landsman, C Huerta Alderete, NH Nguyen, AY Matsuura, TH Hsieh, and C Monroe, “Generation of thermofield double states and critical ground states with a quantum computer,” Proceedings of the National Academy of Sciences 117
2020
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2020
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2020
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2020
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2020
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2020
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2020
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2020
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2020
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Jonas Haferkamp, Dominik Hangleiter, Adam Bouland, Bill Fefferman, Jens Eisert, and Juani Bermejo-Vega, “Closing gaps of a quantum advantage with short-time hamiltonian dynamics,” Physical Review Letters 125
2020
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Eliska Greplova, Agnes Valenti, Gregor Boschung, Frank Schäfer, Niels Lörch, and Sebastian D Huber, “Unsupervised identification of topological phase transitions using predictive models,” New Journal of Physics 22
2020
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Adriano Macarone Palmieri, Egor Kovlakov, Federico Bianchi, Dmitry Yudin, Stanislav Straupe, Jacob D Biamonte, and Sergei Kulik, “Experimental neural network enhanced quantum tomography,” npj Quantum Information 6
2020
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Yi Zhang, Paul Ginsparg, and Eun-Ah Kim, “Interpreting machine learning of topological quantum phase transitions,” Physical Review Research 2
2020
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2020
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2020
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Agnes Valenti, Guliuxin Jin, Julian Leonard, Sebastian D. Huber, and Eliska Greplova, “Manybodydynlearning,” https://gitlab.com/QMAI/papers/manybodydynlearning (2021)
2021
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