研究生: |
蕭鈺鈴 Yu-Ling Hsiao |
---|---|
論文名稱: |
在量子網路中最大化吞吐量之糾纏分配方法 Entanglement Distribution Approaches for Maximizing Throughput in a Quantum Network |
指導教授: |
賴源正
Yuan-Cheng Lai |
口試委員: |
林伯慎
Bor-Shen Lin 陳彥宏 Yen-Hung Chen |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 資訊管理系 Department of Information Management |
論文出版年: | 2023 |
畢業學年度: | 111 |
語文別: | 英文 |
論文頁數: | 45 |
中文關鍵詞: | 量子網路 、量子路由 、資源分配 、糾纏分配 |
外文關鍵詞: | quantum network, quantum routing, resource allocation, entanglement distribution |
相關次數: | 點閱:323 下載:2 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
現今量子技術正受到世界各地許多學術和工業組織的關注,隨著處理器的量子位元數量增多,能夠實現一些傳統運算或網路沒辦法做到的應用。然而,由於量子機制中無法複製的特性,一旦對量子位元進行複製必定會改變它原本的狀態,此時就要透過量子隱形傳態的方式來傳遞量子訊息。在量子隱形傳態中需要在來源端和目的端共享糾纏對,產生糾纏對的方式有三種,集中式、端對端和兩個端點,產生後需要將糾纏對傳遞至來源端和目的端,此時有效的路由以及糾纏對的分配可以減少資源競爭和壅塞的情況,然而目前的研究大多都只採用一種產生方式來提供糾纏對。
本論文提出兩個在多請求及多路徑之量子網路做糾纏對分配的方法,分別是PU with Hungriest Path First (PU-HPF)和Shortest Path First with PU (SPF-PU),並在原本兩個端點的架構上再加入集中式的方式提供糾纏對,希望能夠在有限的糾纏對下達到最大的吞吐量。PU-HPF先分配兩個端點產生的糾纏對,再分配集中式的糾纏對,其依照請求的飢餓程度,作為獲得糾纏對的優先順序;而SPF-PU則不論糾纏對為兩個端點還是集中式所產生的,皆同時進行分配。在每一次分配時都會採用該請求的最短路徑,並確保分配到的糾纏對不會超過請求需求量和集中式方法所提供的糾纏對。分析結果顯示,SPF-PU表現最佳,相較於僅採用兩端點產生糾纏對的方式和PU-HPF,分別增加31.5% 和22.4%的吞吐量。
Nowadays, various academic and industrial organizations worldwide study quantum technology. With an increasing number of qubits in processors, it is possible to enable applications that classical networks cannot accomplish. However, due to the no-cloning theorem, which forbids the creation of identical copies of an arbitrary qubit, quantum teleportation is employed to transmit quantum information. Quantum teleportation requires the entangled pair of qubits between the source and destination nodes. Currently, there are three approaches to generate entangled pairs: centralized, end-to-end, and both end-points. The entangled pairs need to be transmitted to the two remote nodes. At this stage, effective routing and entangled pairs distribution can reduce congestion. However, most current research primarily uses a single approach to generate entangled pairs.
This paper proposes two entangled pairs distributions in a multi-request and multi-path quantum network: PU with Hungriest Path First (PU-HPF) and Shortest Path First with PU (SPF-PU). The centralized and both end-points approaches both provide entangled pairs for maximizing throughput. PU-HPF distributes both end-points first and then centralized resources. The distribution priority is determined based on the order of hungry levels. SPF-PU distributes both end-points and centralized resources simultaneously by selecting the shortest paths for each flow. The results demonstrate that SPF-PU outperforms the method that adopts both end-points to generate entangled pairs and PU-HPF by improving the throughput of 31.5% and 22.4%, respectively.
[1] S. Wehner, D. Elkouss, and R. Hanson, “Quantum internet: A vision for the road ahead”, Science, vol. 362, no. 6412, pp. eaam9288, 2018.
[2] C. L. Degen, F. Reinhard, and P. Cappellaro, “Quantum sensing”, Rev. Mod. Phys., vol. 89, pp. 035002, 2017.
[3] C. H. Bennett, G. Brassard, C. Crépeau, R. Jozsa, A. Peres, and W. K. Wootters, “Teleporting an unknown quantum state via dual classical and Einstein-Podolsky-Rosen channels”, Phys. Rev. Lett., vol. 70, pp. 1895–1899, 1993.
[4] A. S. Cacciapuoti, M. Caleffi, R. Van Meter and L. Hanzo, “When Entanglement Meets Classical Communications: Quantum Teleportation for the Quantum Internet,” IEEE Transactions on Communications, vol. 68, no. 6, pp. 3808-3833, 2020.
[5] A. S. Cacciapuoti, M. Caleffi, F. Tafuri, F. S. Cataliotti, S. Gherardini, and G. Bianchi, “Quantum Internet: Networking Challenges in Distributed Quantum Computing”, IEEE Network, vol. 34, no. 1, pp. 137–143, 2020.
[6] M. Caleffi, D. Chandra, D. Cuomo, S. Hassanpour, and A. S. Cacciapuoti, “The Rise of the Quantum Internet”, Computer, vol. 53, no. 6, pp. 67–72, 2020.
[7] R. Van Meter, T. Satoh, T. D. Ladd, W. J. Munro, and K. Nemoto, “Path selection for quantum repeater networks”, Networking Science, vol. 3, no. 1, pp. 82–95, 2013.
[8] M. Caleffi, “Optimal routing for quantum networks”, IEEE Access, vol. 5, pp. 22299–22312, 2017.
[9] L. Gyongyosi and S. Imre, “Decentralized base-graph routing for the quantum internet”, Physical Review A, vol. 98, no. 2, pp. 022310, 2018.
[10] K. Chakraborty, F. Rozpedek, A. Dahlberg, and S. Wehner, “Distributed routing in a quantum internet”, arXiv preprint arXiv:1907. 11630, 2019.
[11] M. Pant et al., “Routing entanglement in the quantum internet”, npj Quantum Information, vol. 5, no. 1, pp. 1–9, 2019.
[12] K. Chakraborty, D. Elkouss, B. Rijsman, and S. Wehner, “Entanglement Distribution in a Quantum Network: A Multicommodity Flow-Based Approach”, IEEE Transactions on Quantum Engineering, vol. 1, pp. 1–21, 2020.
[13] S. Pirandola, “End-to-end capacities of a quantum communication network”, Communications Physics, vol. 2, no. 1, pp. 51, 2019.
[14] S. Shi and C. Qian, “Concurrent entanglement routing for quantum networks: Model and designs”, Proceedings of the Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication, pp. 62–75, 2020.
[15] C. Cicconetti, M. Conti, and A. Passarella, “Resource Allocation in Quantum Networks for Distributed Quantum Computing”, in 2022 IEEE International Conference on Smart Computing (SMARTCOMP), pp. 124–132, 2022.
[16] N. Ngoenriang et al., “Optimal stochastic resource allocation for distributed quantum computing”, arXiv [cs.DC], 2022.
[17] Y. Gao, S. Yang, F. Li, and X. Fu, “Adaptive and Efficient Qubit Allocation Using Reinforcement Learning in Quantum Networks”, IEEE Network, vol. 36, no. 5, pp. 48–54, 2022.
[18] C. Li, T. Li, Y.-X. Liu, and P. Cappellaro, “Effective routing design for remote entanglement generation on quantum networks”, npj Quantum Information, vol. 7, no. 1, pp. 1–12, 2021.