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摘要:
Grover’s search algorithm is one of the most significant quantum algorithms,which can obtain quadratic speedup of the extensive search problems.Since Grover's search algorithm cannot be implemented on a real quantum computer at present,its quantum simulation is regarded as an effective method to study the search performance.When simulating the Grover's algorithm,the storage space required is exponential,which makes it difficult to simulate the high-qubit Grover’s algorithm.To this end,we deeply study the storage problem of probability amplitude,which is the core of the Grover simulation algorithm.We propose a novel memory-efficient method via amplitudes compression,and validate the effectiveness of the method by theoretical analysis and simulation experimentation.The results demonstrate that our compressed simulation search algorithm can help to save nearly 87.5%of the storage space than the uncompressed one.Thus under the same hardware conditions,our method can dramatically reduce the required computing nodes,and at the same time,it can simulate at least 3 qubits more than the uncompressed one.Particularly,our memory-efficient simulation method can also be used to simulate other quantum algorithms to effectively reduce the storage costs required in simulation.
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篇名 A Memory-efficient Simulation Method of Grover’s Search Algorithm
来源期刊 计算机、材料和连续体(英文) 学科 工学
关键词 Grover’s SEARCH ALGORITHM PROBABILITY AMPLITUDE QUANTUM simulation MEMORY compression
年,卷(期) 2018,(11) 所属期刊栏目
研究方向 页码范围 307-319
页数 13页 分类号 TP3
字数 语种
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研究主题发展历程
节点文献
Grover’s
SEARCH
ALGORITHM
PROBABILITY
AMPLITUDE
QUANTUM
simulation
MEMORY
compression
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研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
计算机、材料和连续体(英文)
月刊
1546-2218
江苏省南京市浦口区东大路2号东大科技园A
出版文献量(篇)
346
总下载数(次)
4
总被引数(次)
0
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