SHENZHEN, China, March 13, 2025 /PRNewswire/ — MicroAlgo Inc. (the “Company” or “MicroAlgo”) (NASDAQ: MLGO), today announced that their research team has used quantum neural networks to classify and extract features from data in databases, focusing the search space on subsets that are more likely to contain the target. By leveraging feature extraction and pattern recognition techniques in quantum machine learning, they preprocess and filter the features of the database in advance, narrowing down the search range. Grover’s algorithm is then applied for precise searching, thereby improving search efficiency.
Quantum Neural Networks, an emerging technology that combines the principles of quantum mechanics with the architecture of artificial neural networks, are capable of running complex learning algorithms on quantum bits, enabling high-speed data processing and optimization analysis. By simulating the neural network structure of the human brain and integrating quantum superposition and entanglement states, they achieve nonlinear data mapping and advanced abstraction, significantly enhancing the efficiency of pattern recognition and classification.
MicroAlgo’s Quantum Neural Network-based intelligent search system follows a sophisticated process framework, ensuring effective data filtering and efficient processing.
Data Preprocessing: Using advanced quantum pattern recognition technology, the raw data is initially filtered to remove irrelevant information, extract core features, and form a dataset that is easy to index.
Feature Extraction: Leveraging the deep learning capabilities of quantum neural networks, the system automatically uncovers hidden correlations within the data, constructing multi-level feature representations to lay the foundation for subsequent searches.
Subset Focusing: Based on the preliminary feature analysis, the search space is finely segmented to identify potential subsets where the target is likely to be, significantly reducing unnecessary computations.
Applying Grover’s Algorithm: For the preselected subsets, Grover’s algorithm is directly employed, utilizing its quantum parallel search advantages to quickly locate the target and achieve efficient retrieval.
Result Feedback and Optimization: For each search result, the system automatically evaluates its effectiveness, optimizes the search strategy, and iteratively improves the quantum neural network model, continuously enhancing both accuracy and efficiency.
Thanks to the quantum parallel processing mechanism, the quantum neural network intelligent search developed by MicroAlgo outperforms conventional algorithms by a significant margin, especially in the context of big data, where the performance gap becomes even more pronounced. With the support of deep learning technologies, the system has a more profound understanding of the data, enabling it to identify targets with greater accuracy and avoid missed detections or false positives. The combination of quantum neural networks and Grover’s algorithm enhances adaptability, making the search system capable of self-learning, automatically adjusting search strategies with data changes, and maintaining long-term effectiveness.
The integration of quantum neural networks with Grover’s algorithm has broad application prospects. In the field of database search, this technology can significantly improve search efficiency, reduce search costs, and bring revolutionary changes to database management. Additionally, this technology can also be applied in areas such as big data analysis, information security, and bioinformatics, offering new solutions for data processing and analysis in these fields.
In the future, as quantum technology continues to mature, MicroAlgo is expected to further expand the application boundaries of this technology, such as integrating it with more emerging technologies to create a completely new paradigm for intelligent data analysis. The steady increase in the number of quantum bits and the continuous improvement in computational precision will help solve more complex and challenging real-world problems, leading data processing and search technologies to new heights and deeply empowering various industries.
About MicroAlgo Inc.
MicroAlgo Inc. (the “MicroAlgo”), a Cayman Islands exempted company, is dedicated to the development and application of bespoke central processing algorithms. MicroAlgo provides comprehensive solutions to customers by integrating central processing algorithms with software or hardware, or both, thereby helping them to increase the number of customers, improve end-user satisfaction, achieve direct cost savings, reduce power consumption, and achieve technical goals. The range of MicroAlgo’s services includes algorithm optimization, accelerating computing power without the need for hardware upgrades, lightweight data processing, and data intelligence services. MicroAlgo’s ability to efficiently deliver software and hardware optimization to customers through bespoke central processing algorithms serves as a driving force for MicroAlgo’s long-term development.
Forward-Looking Statements
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