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A Phase Estimation Algorithm for Quantum Speed-Up Multi-Party Computing

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摘要 Security and privacy issues have attracted the attention of researchers in the field of IoT as the information processing scale grows in sensor networks.Quantum computing,theoretically known as an absolutely secure way to store and transmit information as well as a speed-up way to accelerate local or distributed classical algorithms that are hard to solve with polynomial complexity in computation or communication.In this paper,we focus on the phase estimation method that is crucial to the realization of a general multi-party computing model,which is able to be accelerated by quantum algorithms.A novel multi-party phase estimation algorithm and the related quantum circuit are proposed by using a distributed Oracle operator with iterations.The proved theoretical communication complexity of this algorithm shows it can give the phase estimation before applying multi-party computing efficiently without increasing any additional complexity.Moreover,a practical problem of multi-party dating investigated shows it can make a successful estimation of the number of solution in advance with zero communication complexity by utilizing its special statistic feature.Sufficient simulations present the correctness,validity and efficiency of the proposed estimation method.
出处 《Computers, Materials & Continua》 SCIE EI 2021年第4期241-252,共12页 计算机、材料和连续体(英文)
基金 Supported by the National Natural Science Foundation of China under Grant Nos.61501247,61373131 and 61702277,the Six Talent Peaks Project of Jiangsu Province(Grant No.2015-XXRJ-013) Natural Science Foundation of Jiangsu Province(Grant No.BK20171458) the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(China under Grant No.16KJB520030) the NUIST Research Foundation for Talented Scholars under Grant Nos.2015r014,PAPD and CICAEET funds funded in part by the Science and Technology Development Fund,Macao SAR(File No.SKL-IOTSC-2018-2020,0018/2019/AKP,0008/2019/AGJ,and FDCT/194/2017/A3) in part by the University of Macao under Grant Nos.MYRG2018-00248-FST and MYRG2019-0137-FST.
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