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We investigate how the computational difficulty of contracting tensor networks depends on the sign structure of the tensor entries.
1906
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1908
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1908
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S. L. Braunstein, C. M. Caves, R. Jozsa, N. Linden, S. Popescu, and R. Schack, Separability of Very Noisy Mixed States and Implications for NMR Quantum Computing , Phys. Rev. Lett. 83
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F. Verstraete and J. I. Cirac, Renormalization algorithms for Quantum-Many Body Systems in two and higher dimensions , (2004), cond-mat/0407066
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J. Kempe, A. Kitaev, and O. Regev, The Complexity of the Local Hamiltonian Problem , SIAM Journal of Computing 35
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P. Hayden, D. W. Leung, and A. Winter, Aspects of Generic Entanglement , Commun. Math. Phys. 265
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J. Eisert, Computational Difficulty of Global Variations in the Density Matrix Renormalization Group , Phys. Rev. Lett. 97
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N. Schuch, M. M. Wolf, F. Verstraete, and J. I. Cirac, The computational complexity of PEPS , Phys. Rev. Lett. 98
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2015
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F. Becca and S. Sorella, Quantum Monte Carlo Approaches for Correlated Systems (Cambridge University Press, 2017)
2017
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2008
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2009
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2013
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S. Gharibian, Y. Huang, Z. Landau, and S. W. Shin, Quantum Hamiltonian Complexity (2015)
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2015
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G. Evenbly and G. Vidal, Tensor Network Renormalization , Phys. Rev. Lett. 115
2015
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2018
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2019
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2019
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2019
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2021
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M. C. Bañuls, Tensor Network Algorithms: A Route Map , Annual Review of Condensed Matter Physics 14
2023
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2023
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