An efficient quantum circuit implementation of Shor’s algorithm for GPU accelerated simulation
Source abstract
Abstract
In this study, we introduce a novel implementation of Shor’s algorithm specifically designed for the Graphics Processing Unit (GPU) acceleration framework. Our focus lies on achieving efficient execution of the modular multiplication circuit through GPU simulation. To seamlessly integrate our design into the PyQPanda library framework, we made necessary modifications, making a deliberate trade-off by sacrificing a small number of quantum resources to leverage the advantages of GPU acceleration. Subsequently, we conducted simulations and rigorously validated the functionality of our circuit using the PyQPanda library, resulting in a significant speedup compared to a central processing unit-only mode.
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Research context
OpenAlex topics: Quantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum-Dot Cellular Automata
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Affiliations
School of Computer Science, Guangdong University of Technology 1 , Guangzhou 510006, China
School of Integrated Circuits, Guangdong University of Technology 2 , Guangzhou 510006, China
Funding
Key-Area Research and Development Program of Guangdong Province
References (19)
Show source-provided references
1. A. M. Dalzell , S.McArdle, M.Berta, P.Bienias, C.-F.Chen, A.Gilyén, C. T.Hann, M. J.Kastoryano, E. T.Khabiboulline, A.Kubica, G.Salton, S.Wang, and F. G. S. L.Brandão, “Quantum algorithms: A survey of applications and end-to-end complexities,” arXiv:2310.03011 [quant-ph] (2023).
2. Quantum networks for elementary arithmetic operations10.1103/PhysRevA.54.147 ↗
3. T. G. Draper , “Addition on a quantum computer,” arXiv:quant-ph/0008033 (2000).
4. P. Kaye , “Reversible addition circuit using one ancillary bit with application to quantum computing,” arXiv:quant-ph/0408173 (2004).
5. S. A. Cuccaro , T. G.Draper, S. A.Kutin, and D. P.Moulton, “A new quantum ripple-carry addition circuit,” arXiv:quant-ph/0410184 (2004).
6. A quantum circuit for Shor’s factoring algorithm using 2n + 2 qubits10.26421/qic6.2-4 ↗
7. Improved quantum ripple-carry addition circuit10.1007/s11432-015-5411-x ↗
8. R. Rines and I.Chuang, “High performance quantum modular multipliers,” arXiv:1801.01081 [quant-ph] (2018).
9. X. Liu , H.Yang, and L.Yang, “CNOT-count optimized quantum circuit of the Shor’s algorithm,” arXiv:2112.11358 [quant-ph] (2021).
10. A method for obtaining digital signatures and public-key cryptosystems10.1145/359340.359342 ↗
11. 2014
12. Large-scale simulation of Shor’s quantum factoring algorithm10.3390/math11194222 ↗
13. M. Ekerå , “On the success probability of quantum order finding,” arXiv:2201.07791 [quant-ph] (2022).
14. Quantum computation and quantum information10.1063/1.1428442 ↗
15. Factoring using 2n + 2 qubits with Toffoli based modular multiplication
16. MPMCT gate decomposition method reducing T-depth quickly in proportion to the number of work qubits10.1007/s11128-023-04142-7 ↗
17. Circuit for Shor’s algorithm using 2n + 3 qubits10.26421/qic3.2-8 ↗
18. Semiclassical Fourier transform for quantum computation10.1103/physrevlett.76.3228 ↗
19. M. Dou , T.Zou, Y.Fang, J.Wang, D.Zhao, L.Yu, B.Chen, W.Guo, Y.Li, Z.Chen, and G.Guo, “QPanda: High-performance quantum computing framework for multiple application scenarios,” arXiv:2212.14201 [quant-ph] (2022).