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Compared with the quantum gate circuit model, the measurement-based quantum computing model provides an alternative way to realize universal quantum computation, and relevant contents have been greatly enriched after nearly two decades of research and exploration. In this article, we review the research history and status of the measurement-based quantum computing model. First, we briefly introduce the basic theories of this model, including the concept and working principles of quantum graph states as resource states, the model’s computational universality and classical simulation methods, and relevant applications in the field of quantum information processing such as designing quantum algorithms and fault-tolerant error correction schemes. Then, from the perspective of quantum physical properties, which include the specific roles of quantum entanglement, contextuality, quantum correlations, symmetry-protected topological order, and quantum phases of matter as computing resources, the close relationship between measurement-based quantum computing model and quantum many-body system is presented. For example, a type of measurement-based computing model for exploiting quantum correlations can show a quantum advantage over the classical local hidden variable models, or certain symmetry-protected topological order states enable the universal quantum computation to be conducted by using only the measurements of single-qubit Pauli operators. Next, a variety of different technical routes and experimental progress of realizing the measurement-based quantum computing model are summarized, such as photonic systems, ion traps, superconducting circuits, etc. These achievements in various physical areas lay the foundation for future scalable and fault-tolerant quantum computers. Finally, we discuss and prospect the future research directions in this field thereby inspiring readers to further study and explore the relevant subjects.
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Keywords:
- quantum computation /
- quantum entanglement /
- quantum correlations /
- symmetry-protected topological order
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图 2 单向量子计算执行量子门操作 (a)输入态
$ \left| + \right\rangle $ 经过${R_z}( - \alpha )$ 旋转和Hadamard门作用; (b)以测量纠缠态的方式等价地实现(a); (c)为(b)的扩展, 制备并测量4-qubit线性簇态以实现任意的单量子比特旋转门; (d)以4-qubit星形簇态执行CNOT门Figure 2. Realization of quantum gates in the 1 WQC model: (a) Input state
$ \left| + \right\rangle $ undergoes a${R_z}( - \alpha )$ rotation and a Hadamard gate; (b) a circuit equivalent to (a) by measuring an entangled state; (c) a generalization of (b) to prepare and measure a 4-qubit linear cluster state for implementing arbitrary single-qubit rotation gates; (d) a circuit performing the CNOT gate via a star cluster state.图 3 基于传态的方案实现单量子比特门 (a)一方远程制备态
$U\left| \alpha \right\rangle $ 并通过Bell测量和泡利修正传给另一方, 注意U和Bell测量可以直接合并成新的联合测量; (b)利用制备好的资源态$(I \otimes U)\left| {{\beta _{{\text{00}}}}} \right\rangle $ 来间接执行$U\left| \alpha \right\rangle $ Figure 3. Teleportation-based scheme for implementing any sing-qubit gate: (a) State
$U\left| \alpha \right\rangle $ is remotely prepared at one site and teleported to another site via Bell measurement and Pauli corrections, note here U and Bell measurement can be directly combined into a new joint measurement; (b) the scheme to indirectly implement$U\left| \alpha \right\rangle $ via a prepared resource state$(I \otimes U)\left| {{\beta _{{\text{00}}}}} \right\rangle $ .图 4 利用关联的计算模型. 经典控制计算机提供k个测量设置中的1个作为对关联多方资源态中个体的经典输入(蓝色箭头), 并且接收l个测量结果中的1个(红色箭头)作为输出
Figure 4. A computational model exploiting correlations. The classical control computer provides one of k measurement settings as the classical input (blue arrows) to each of the parties in the correlated resource state and receives one of l possible measurement results (red arrows) as the output.
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[1] Nielsen M A, Chuang I L 2010 Quantum Computation and Quantum Information (New York: Cambridge University Press) pp1−12
[2] Barenco A, Bennett C H, Cleve R, DiVincenzo D P, Margolus N, Shor P, Sleator T, Smolin J A, Weinfurter H 1995 Phys. Rev. A 52 3457Google Scholar
[3] Raussendorf R, Briegel H J 2001 Phys. Rev. Lett. 86 5188Google Scholar
[4] Raussendorf R, Browne D E, Briegel H J 2003 Phys. Rev. A 68 022312Google Scholar
[5] Prevedel R, Walther P, Tiefenbacher F, Böhi P, Kaltenbaek R, Jennewein T, Zeilinger A 2007 Nature 445 65Google Scholar
[6] Lanyon B, Jurcevic P, Zwerger M, Hempel C, Martinez E, Dür W, Briegel H, Blatt R, Roos C F 2013 Phys. Rev. Lett. 111 210501Google Scholar
[7] Tame M, Özdemir Ş, Koashi M, Imoto N, Kim M 2009 Phys. Rev. A 79 020302Google Scholar
[8] Tame M S, Prevedel R, Paternostro M, Böhi P, Kim M, Zeilinger A 2007 Phys. Rev. Lett. 98 140501Google Scholar
[9] Tame M, Kim M 2010 Phys. Rev. A 82 030305Google Scholar
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[12] Pathumsoot P, Matsuo T, Satoh T, Hajdušek M, Suwanna S, Van Meter R 2020 Phys. Rev. A 101 052301Google Scholar
[13] Hein M, Eisert J, Briegel H J 2004 Phys. Rev. A 69 062311Google Scholar
[14] Briegel H J, Browne D E, Dür W, Raussendorf R, Van den Nest M 2009 Nat. Phys. 5 19Google Scholar
[15] Preskill J 2018 Quantum 2 79Google Scholar
[16] Gühne O, Tóth G 2009 Phys. Rep. 474 1Google Scholar
[17] Bennett C H, Brassard G, Crépeau C, Jozsa R, Peres A, Wootters W K 1993 Phys. Rev. Lett. 70 1895Google Scholar
[18] Bouwmeester D, Pan J W, Mattle K, Eibl M, Weinfurter H, Zeilinger A 1997 Nature 390 575Google Scholar
[19] Gottesman D, Chuang I L 1999 Nature 402 390Google Scholar
[20] Perdrix S 2005 Int. J. Quantum Inf. 3 219Google Scholar
[21] Jorrand P, Perdrix S 2005 Proc. SPIE 5833 44Google Scholar
[22] Gross D, Eisert J 2007 Phys. Rev. Lett. 98 220503Google Scholar
[23] Gross D, Eisert J, Schuch N, Perez-Garcia D 2007 Phys. Rev. A 76 052315Google Scholar
[24] Danos V, Kashefi E 2006 Phys. Rev. A 74 052310Google Scholar
[25] van den Nest M, Dür W, Miyake A, Briegel H 2007 New J. Phys. 9 204Google Scholar
[26] Danos V, Kashefi E, Panangaden P 2007 J. ACM 54 8Google Scholar
[27] Briegel H J, Raussendorf R 2001 Phys. Rev. Lett. 86 910Google Scholar
[28] Hein M, Dür W, Eisert J, Raussendorf R, Nest M, Briegel H J 2006 arXiv: 0602096 [quant-ph]
[29] Walther P, Resch K J, Rudolph T, et al. 2005 Nature 434 169Google Scholar
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[31] Van den Nest M, Miyake A, Dür W, Briegel H J 2006 Phys. Rev. Lett. 97 150504Google Scholar
[32] Nielsen M A 2006 Rep. Math. Phys. 57 147Google Scholar
[33] Browne D E, Rudolph T 2005 Phys. Rev. Lett. 95 010501Google Scholar
[34] Bell B, Tame M, Clark A, Nock R, Wadsworth W, Rarity J G 2013 New J. Phys. 15 053030Google Scholar
[35] Leung D W 2004 Int. J. Quantum Inf. 2 33Google Scholar
[36] Aliferis P, Leung D W 2004 Phys. Rev. A 70 062314Google Scholar
[37] Childs A M, Leung D W, Nielsen M A 2005 Phys. Rev. A 71 032318Google Scholar
[38] Verstraete F, Cirac J I 2004 Phys. Rev. A 70 060302Google Scholar
[39] Nielsen M A 2004 Phys. Rev. Lett. 93 040503Google Scholar
[40] Zwerger M, Briegel H, Dür W 2014 Sci. Rep. 4 5364Google Scholar
[41] Vidal G 2003 Phys. Rev. Lett. 91 147902Google Scholar
[42] Markov I L, Shi Y 2008 SIAM J. Comput. 38 963Google Scholar
[43] Jozsa R 2006 arXiv: 0603163 [quant-ph]
[44] Shi Y Y, Duan L M, Vidal G 2006 Phys. Rev. A 74 022320Google Scholar
[45] van den Nest M, Dür W, Vidal G, Briegel H J 2007 Phys. Rev. A 75 012337Google Scholar
[46] Yoran N, Short A J 2006 Phys. Rev. Lett. 96 170503Google Scholar
[47] Bravyi S, Raussendorf R 2007 Phys. Rev. A 76 022304Google Scholar
[48] Zhang S, Zhang Y, Sun Y, Sun H, Zhang X 2019 Opt. Express 27 436Google Scholar
[49] Chen M C, Li R, Gan L, Zhu X, Yang G, Lu C Y, Pan J W 2020 Phys. Rev. Lett. 124 080502Google Scholar
[50] Chen K, Li C M, Zhang Q, Chen Y A, Goebel A, Chen S, Mair A, Pan J W 2007 Phys. Rev. Lett. 99 120503Google Scholar
[51] Raussendorf R 2013 Phys. Rev. A 88 022322Google Scholar
[52] Oestereich A L, Galvão E F 2017 Phys. Rev. A 96 062305Google Scholar
[53] Raussendorf R, Briegel H J 2002 Quantum Inf. Comput. 2 443
[54] Broadbent A, Kashefi E 2009 Theor. Comput. Sci. 410 2489Google Scholar
[55] Browne D, Kashefi E, Perdrix S 2010 Conference on Quantum Computation, Communication, and Cryptography Leeds, UK, April 2010 pp35−46
[56] Raussendorf R 2003 Ph. D. Dissertation (Munich: LMU)
[57] Nielsen M A, Dawson C M 2005 Phys. Rev. A 71 042323Google Scholar
[58] Dawson C M, Haselgrove H L, Nielsen M A 2006 Phys. Rev. Lett. 96 020501Google Scholar
[59] Raussendorf R, Harrington J, Goyal K 2006 Ann. Phys. 321 2242Google Scholar
[60] Raussendorf R, Harrington J, Goyal K 2007 New J. Phys. 9 199Google Scholar
[61] Raussendorf R, Harrington J 2007 Phys. Rev. Lett. 98 190504Google Scholar
[62] Devitt S J, Fowler A G, Stephens A M, Greentree A D, Hollenberg L C, Munro W J, Nemoto K 2009 New J. Phys. 11 083032Google Scholar
[63] Herrera-Martí D A, Fowler A G, Jennings D, Rudolph T 2010 Phys. Rev. A 82 032332Google Scholar
[64] Yao X C, Wang T X, Chen H Z, et al. 2012 Nature 482 489Google Scholar
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[66] Broadbent A, Fitzsimons J, Kashefi E 2009 Proceedings of the 50th Annual IEEE Symposium on Foundations of Computer Science pp517−526
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