|
|
|
Distributed quantum circuit partitioning and teleportation optimization based on a multi-dimensional evaluation strategy |
| Le Zhang(张乐)1, Zhijin Guan(管致锦)2,1,†, Shuo Qin(秦硕)1, Zheng Luo(罗政)1, Fei Ding(丁飞)1, and Xueyun Cheng(程学云)1,‡ |
1 School of Artificial Intelligence and Computer Science, Nantong University, Nantong 226019, China;
2 College of Engineering the Internet of Things, Taihu University, Wuxi 214063, China |
|
|
|
|
Abstract Distributed quantum computing has emerged as a key approach to extending current quantum computing capabilities, with its performance largely determined by the cost of qubit transmissions across physical nodes. To minimize such cross-partition transmission costs, this paper proposes a distributed quantum circuit partitioning and teleportation optimization method based on a multidimensional evaluation strategy. First, a scoring function is designed using interaction strength and temporal fragmentation, guiding the partitioning process to balance structural compactness with temporal continuity. Building on this, we employ multiple starting points and parameter search strategies to progressively construct candidate partition schemes. Subsequently, a transmission-cost optimization method based on teleportation group partitioning is introduced to evaluate candidates more accurately, taking into account gate timing, interfering operations, and communication resource conflicts, thereby yielding a more realistic estimate of teleportation counts. Simulation results on several benchmark quantum circuits demonstrate that the proposed method consistently generates superior partitions under challenging conditions, such as high interaction density and significant gate interleaving. In some cases, teleportation counts are reduced by up to 64.7%, with an overall average improvement of 8%, verifying the adaptability and effectiveness of the method in optimizing communication across different interaction structures.
|
Received: 07 September 2025
Revised: 20 October 2025
Accepted manuscript online:
|
|
PACS:
|
03.67.-a
|
(Quantum information)
|
| |
03.67.Ac
|
(Quantum algorithms, protocols, and simulations)
|
| |
03.67.Hk
|
(Quantum communication)
|
| |
03.67.Lx
|
(Quantum computation architectures and implementations)
|
|
| Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62072259), in part by the Natural Science Foundation of Jiangsu Province (Grant No. BK20221411), in part by the Natural Science Foundation of Nantong (Grant No. JC2024100), and in part by the Ph.D. Start-up Fund of Nantong University (Grant No. 23B03). |
Corresponding Authors:
Zhijin Guan, Xueyun Cheng
E-mail: guan.zj@ntu.edu.cn;chen.xy@ntu.edu.cn
|
Cite this article:
Le Zhang(张乐), Zhijin Guan(管致锦), Shuo Qin(秦硕), Zheng Luo(罗政), Fei Ding(丁飞), and Xueyun Cheng(程学云) Distributed quantum circuit partitioning and teleportation optimization based on a multi-dimensional evaluation strategy 2026 Chin. Phys. B 35 050305
|
[1] Memon Q A, Al Ahmad M and Pecht M 2024 Quantum Rep. 6, 627
[2] Stassi R, Cirio M and Nori F 2020 npj Quantum Information 6, 67
[3] Hamilton M C, Yelamanchili B, Shah A, Peek S E, Bankson S and Tillman C C 2022 Superconducting Microwave Interconnect Technologies for Quantum and Cryogenic Systems, IEEE/MTT-S International Microwave Symposium (IMS), 72
[4] Polikarpov P V, Uvarov N K and Khomonenko A D 2021 Intell. Transp. Syst. Transp. Security 1, 33
[5] AbuGhanem M 2024 arXiv:2410.00916 [quant-ph]
[6] Preskill J 2018 Quantum 2, 79
[7] Monroe C, Raussendorf R, Ruthven A, Brown K R, Maunz P, Duan L M and Kim J 2014 Phys. Rev. A 89, 022317
[8] Chou K S, Blumoff J Z, Wang C S, Reinhold P C, Axline C J, Gao Y Y and Schoelkopf R J 2018 Nature 561, 368
[9] Ghodsollahee I, Davarzani Z, Zomorodi M, Pawiak P, Houshmand M and Houshmand M 2021 Quantum Inf. Process. 20, 235
[10] Andres-Martinez P and Heunen C 2019 Phys. Rev. A 100, 032308
[11] Dadkhah D, Zomorodi M and Hosseini S E 2022 IEEE Access 10, 70329
[12] Nikahd E, Mohammadzadeh N, SedighiMand ZamaniMS 2021 Phys. Scr. 96, 035102
[13] Davarzani Z, ZomorodiMand Houshmand M 2022 Sci. Rep. 12, 15421
[14] Zomorodi-Moghadam M, Houshmand M and Houshmand M 2018 Int. J. Theor. Phys. 57, 848
[15] Daei O, Navi K and Zomorodi-Moghadam M 2020 Int. J. Theor. Phys. 59, 3804
[16] Zhong Y, Chang H S, Bienfait A, Dumur E, Chou M H, Conner C R, Grebel J, Povey R G, Yan H, Schuster D I and Cleland A N 2021 Nature 590, 571
[17] Chen X, Chen Z, Zhu P, Cheng X and Guan Z 2025 IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.
[18] Chen Z, Chen X, Jiang Y, Cheng X and Guan Z 2023 Int. J. Theor. Phys. 62, 255
[19] Daei O, Navi K and Zomorodi M 2018 Int. J. Theor. Phys. 60, 3494
[20] Pirandola S, Eisert J, Weedbrook C, Furusawa A and Braunstein S L 2015 Nature Photonics 9, 641
[21] Brown K R, Kim J and Monroe C 2016 npj Quantum Information 2, 1
[22] Jozsa R 2004 IBM J. Res. Dev. 48, 79
[23] Verma V and Prakash H 2016 Int. J. Theor. Phys. 55, 2061 |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|
