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Quantum state tomography (QST) is the art of reconstructing an unknown quantum state through measurements.
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2022
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I. L. Gutiérrez and C. B. Mendl, Real time evolution with neural-network quantum states, Quantum 6
2022
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J. Choi, A. L. Shaw, I. S. Madjarov, X. Xie, R. Finkelstein, J. P. Covey, J. S. Cotler, D. K. Mark, H.-Y. Huang, A. Kale, et al. , Preparing random states and benchmarking with many-body quantum chaos, Nature 613
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A. Elben, S. T. Flammia, H.-Y. Huang, R. Kueng, J. Preskill, B. Vermersch, and P. Zoller, The randomized measurement toolbox, Nature Reviews Physics 5
2023
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V. Havlicek, Amplitude ratios and neural network quantum states, Quantum 7
2023
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Y. Y. Atas, J. F. Haase, J. Zhang, V. Wei, S. M.-L. Pfaendler, R. Lewis, and C. A. Muschik, Simulating one-dimensional quantum chromodynamics on a quantum computer: Real-time evolutions of tetra-and pentaquarks, Physical Review Research 5
2023
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H.-Y. Hu, S. Choi, and Y.-Z. You, Classical shadow tomography with locally scrambled quantum dynamics, Physical Review Research 5
2023
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M. Hibat-Allah, R. G. Melko, and J. Carrasquilla, Investigating topological order using recurrent neural networks, Physical Review B 108
2023
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S. Becker, N. Datta, L. Lami, and C. Rouzé, Classical shadow tomography for continuous variables quantum systems, IEEE Transactions on Information Theory (2024)
2024
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