Industry Background

Industry Background

The big data technology is leaping forward, asking for higher computing efficiency. Generally speaking, big data has a large volume, comes in various types, can be quickly processed and is of low value density. The explosive growth of big data and the limitation of Moore's Law pose huge challenges to classic computers, whereas quantum computing opens a new horizon for big data development with its unique characteristics. The advantage of applying quantum computing to big data lies in that it breaks the computational limit of the Turing Machine, which not only reduces the complexity of problems, but also improves computing efficiency and computing performance exponentially.

Application Scenarios

Application Scenarios

Data Search

It takes the traditional algorithm O(N) time to process an unordered database with N elements, while quantum algorithm can finish the task in O(√N) time. For an unordered database with 100 million elements, it only takes 10,000 operations to retrieve the target value.

Application Scenarios

Cluster Analysis

Two methods are available for optimizing clustering analysis in a quantum manner, including the classical clustering algorithm accelerated by the Grover algorithm, and the quantum dynamics clustering analysis developed from the principles of quantum mechanics.

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Cooperation Cases

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Hefei Big Data Assets Operation Company

Jointly explore the application of quantum computing in big data based on the OriginQ cloud platform, quantum software, and etc.

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Guangdong Hua-shao-shu-zhi Technology Co., Ltd.

Explore and collaborate on the application of quantum computer prototypes, quantum software and algorithms in big data centers.