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MicroAlgo Inc. Adopts Quantum Phase Estimation (QPE) Method to Enhance Quantum Neural Network Training
MLGOMicroAlgo (MLGO) Prnewswire· Prnewswire·2025-06-06 14:20

Core Insights - MicroAlgo Inc. is exploring the potential of quantum technology, particularly in training Quantum Neural Networks (QNNs), which could lead to significant advancements in data processing and pattern recognition [1] Quantum Neural Network Training - Quantum Phase Estimation (QPE) is a crucial technique in quantum computing that enhances the training efficiency of neural networks by optimizing network parameters through precise phase estimation [2][10] - The construction of quantum circuits is essential for mapping the neural network's structure, ensuring accurate representation of parameters [3] - Quantum state initialization involves applying quantum gate operations to set qubits in specific states that correspond to the neural network's initial parameters [4] - Controlled unitary operations are utilized to entangle the neural network's parameters with auxiliary qubits, gradually accumulating phase information [5] - The inverse Quantum Fourier Transform is applied to convert quantum states into classical bit values for parameter optimization [6] Parameter Optimization and Error Correction - Parameter optimization involves adjusting the neural network's parameters based on estimated phase information to improve output accuracy through iterative processes [7] - Advanced quantum error correction techniques are implemented to enhance training stability and precision of phase estimation [8] Applications and Future Prospects - The application of QPE in QNN training has shown to significantly improve image processing capabilities, outperforming traditional methods in speed and accuracy [9] - In natural language processing, optimized network parameters allow for better understanding and generation of text, enhancing efficiency and fluency in various tasks [9] - The scalability of this technology supports the ongoing development of quantum computing and the increasing number of qubits, indicating a promising future for larger-scale QNN training [10][11][12] Company Overview - MicroAlgo Inc. specializes in developing bespoke central processing algorithms, providing comprehensive solutions that integrate these algorithms with software and hardware to enhance customer satisfaction and achieve technical goals [13]