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We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits.
1910
Earlier work this paper cites.
Steven R. White, “Density matrix formulation for quantum renormalization groups,” Phys. Rev. Lett. 69
1992
Earlier work this paper cites.
Steven R. White, “Density-matrix algorithms for quantum renormalization groups,” Phys. Rev. B 48
1993
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P. W. Brouwer and C. W. J. Beenakker, “Diagrammatic method of integration over the unitary group, with applications to quantum transport in mesoscopic systems,” Journal of Mathematical Physics 37
1996
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2001
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2001
Earlier work this paper cites.
A J Daley, C Kollath, U Schollwöck, and G Vidal, “Time-dependent density-matrix renormalization-group using adaptive effective hilbert spaces,” Journal of Statistical Mechanics: Theory and Experiment 2004
2004
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Guifré Vidal, “Efficient simulation of one-dimensional quantum many-body systems,” Phys. Rev. Lett. 93
2004
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Steven R. White and Adrian E. Feiguin, “Real-time evolution using the density matrix renormalization group,” Phys. Rev. Lett. 93
2004
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2005
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2008
Earlier work this paper cites.
Igor L. Markov and Yaoyun. Shi, “Simulating quantum computation by contracting tensor networks,” SIAM Journal on Computing 38
2008
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Hamed Saberi, Andreas Weichselbaum, Lucas Lamata, David Pérez-García, Jan von Delft, and Enrique Solano, “Constrained optimization of sequentially generated entangled multiqubit states,” Phys. Rev. A 80
2009
Earlier work this paper cites.
Yuichi Hirata, Masaki Nakanishi, Shigeru Yamashita, and Yasuhiko Nakashima, “An Efficient Method to Convert Arbitrary Quantum Circuits to Ones on a Linear Nearest Neighbor Architecture,” in 2009 Third International Conference on Quantum, Nano and Micro Technologies (IEEE, 2009) pp. 26–33
2009
Cited alongside, same era.
E M Stoudenmire and Steven R White, “Minimally entangled typical thermal state algorithms,” New Journal of Physics 12
2010
Cited alongside, same era.
U. Schollwöck, “The density-matrix renormalization group in the age of matrix product states,” Annals of Physics 326
2011
Cited alongside, same era.
2014
Cited alongside, same era.
2021
Later among the works it cites.
A. S. Popova and A. N. Rubtsov, “Cracking the quantum advantage threshold for gaussian boson sampling,” (2021)
2021
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Benjamin Villalonga, Murphy Yuezhen Niu, Li Li, Hartmut Neven, John C. Platt, Vadim N. Smelyanskiy, and Sergio Boixo, “Efficient approximation of experimental gaussian boson sampling,” (2021)
2021
Later among the works it cites.
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2017
Cited alongside, same era.
2018
Cited alongside, same era.
Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C. Bardin, Rami Barends, Rupak Biswas, Sergio Boixo, Fernando G. S. L. Brandao, David A. Buell, and et al., “Quantum supremacy using a programmable superconducting processor,” Nature 574
2019
Cited alongside, same era.
Yiqing Zhou, E. Miles Stoudenmire, and Xavier Waintal, “What limits the simulation of quantum computers?” Phys. Rev. X 10
2020
Cited alongside, same era.
Han-Sen Zhong, Hui Wang, Yu-Hao Deng, Ming-Cheng Chen, Li-Chao Peng, Yi-Han Luo, Jian Qin, Dian Wu, Xing Ding, Yi Hu, Peng Hu, Xiao-Yan Yang, Wei-Jun Zhang, Hao Li, Yuxuan Li, Xiao Jiang, Lin Gan, Guangwen Yang, Lixing You, Zhen Wang, Li Li, Nai-Le Liu, Chao-Yang Lu, and Jian-Wei Pan, “Quantum computational advantage using photons,” Science 370
2020
Cited alongside, same era.
2020
Cited alongside, same era.
Yuchen Pang, Tianyi Hao, Annika Dugad, Yiqing Zhou, and Edgar Solomonik, “Efficient 2d tensor network simulation of quantum systems,” in SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (2020) pp. 1–14
2020
Cited alongside, same era.
Johnnie Gray and Stefanos Kourtis, “Hyper-optimized tensor network contraction,” Quantum 5
2021
Cited alongside, same era.
2021
Later among the works it cites.
2021
Later among the works it cites.
Xun Gao, Marcin Kalinowski, Chi-Ning Chou, Mikhail D. Lukin, Boaz Barak, and Soonwon Choi, “Limitations of linear cross-entropy as a measure for quantum advantage,” (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Matija Medvidović and Giuseppe Carleo, “Classical variational simulation of the Quantum Approximate Optimization Algorithm,” npj Quantum Information 7
2021
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2021
Later among the works it cites.
Feng Pan, Keyang Chen, and Pan Zhang, “Solving the sampling problem of the sycamore quantum circuits,” Phys. Rev. Lett. 129
2022
Closest in time.
Changhun Oh, Youngrong Lim, Bill Fefferman, and Liang Jiang, “Classical simulation of boson sampling based on graph structure,” Phys. Rev. Lett. 128
2022
Closest in time.
Maxime Dupont, Nicolas Didier, Mark J. Hodson, Joel E. Moore, and Matthew J. Reagor, “Calibrating the classical hardness of the quantum approximate optimization algorithm,” (2022)
2022
Closest in time.
Rishi Sreedhar, Pontus Vikstål, Marika Svensson, Andreas Ask, Göran Johansson, and Laura García-Álvarez, “The quantum approximate optimization algorithm performance with low entanglement and high circuit depth,” (2022)
2022
Closest in time.