Models in quantum computing: a systematic review

被引:26
作者
Nimbe, Peter [1 ]
Weyori, Benjamin Asubam [1 ]
Adekoya, Adebayo Felix [1 ]
机构
[1] Univ Energy & Nat Resources, POB 214, Sunyani, Ghana
关键词
Quantum computing; Quantum states; Model of computation; Quantum neural networks; Quantum automata; Quantum circuits; INFORMATION; COMPLEXITY;
D O I
10.1007/s11128-021-03021-3
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Quantum computing is computing beyond classical computing based on quantum phenomena such as superposition and entanglement. While quantum computing is still seeking its shape, its effect is seen in making magnificent strides in the field of computing bringing into bare a new dimension of computing. Nevertheless, just like any other concept or field, it has some challenges, and a lot of research and work need to be done to realize its capabilities and benefits. This review provides an insight into quantum computing models coupled with the identification of some pros and cons. The main contribution of this systematic review is that it summarizes the current state-of-the-art models of quantum computing in various domains. It provides new classifications of quantum models based on the literature reviewed and links results to that of the four major categories of quantum computing models. Assessment reveals that most of the models reviewed are either mathematical or algorithmic even though they are based on quantum operations and circuits.
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页数:61
相关论文
共 221 条
[1]  
Aaronson S, 2011, ACM S THEORY COMPUT, P333
[2]   Inhomogeneous driving in quantum annealers can result in orders-of-magnitude improvements in performance [J].
Adame, Juan, I ;
McMahon, Peter L. .
QUANTUM SCIENCE AND TECHNOLOGY, 2020, 5 (03)
[3]   Spin-1 models in the ultrastrong-coupling regime of circuit QED [J].
Albarran-Arriagada, F. ;
Lamata, L. ;
Solano, E. ;
Romero, G. ;
Retamal, J. C. .
PHYSICAL REVIEW A, 2018, 97 (02)
[4]   Temperature Scaling Law for Quantum Annealing Optimizers [J].
Albash, Tameem ;
Martin-Mayor, Victor ;
Hen, Itay .
PHYSICAL REVIEW LETTERS, 2017, 119 (11)
[5]   σ Models on Quantum Computers [J].
Alexandru, Andrei ;
Bedaque, Paulo F. ;
Lamm, Henry ;
Lawrence, Scott .
PHYSICAL REVIEW LETTERS, 2019, 123 (09)
[6]   Quantum Neural Networks: Current Status and Prospects for Development [J].
Altaisky, M. V. ;
Kaputkina, N. E. ;
Krylov, V. A. .
PHYSICS OF PARTICLES AND NUCLEI, 2014, 45 (06) :1013-1032
[7]   1-way quantum finite automata: strengths, weaknesses and generalizations [J].
Ambainis, A ;
Freivalds, R .
39TH ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE, PROCEEDINGS, 1998, :332-341
[8]  
Ambainis A, 2010, QUANTUM PHYS
[9]   Searching for quantum speedup in quasistatic quantum annealers [J].
Amin, Mohammad H. .
PHYSICAL REVIEW A, 2015, 92 (05)
[10]   Error thresholds for Abelian quantum double models: Increasing the bit-flip stability of topological quantum memory [J].
Andrist, Ruben S. ;
Wootton, James R. ;
Katzgraber, Helmut G. .
PHYSICAL REVIEW A, 2015, 91 (04)