SHENZHEN,China, July 7, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced the development of a Grover-based quantum algorithm designed to find pure Nash equilibria in graphical games. This technology represents not only an important advancement in quantum algorithm research but also provides a fresh perspective on game theory and its applications. The Grover search algorithm is an efficient quantum search algorithm that can find a target element in an unstruc ...

文章核心观点 公司将量子图像LSQb算法与量子加密技术集成，提出全新信息隐藏和传输方案，构建更安全高效的数据保护机制，该系统已应用于多领域，未来有望拓展到更多新兴领域 [1][9][11] 技术创新 - 利用LSQb算法进行高效信息编解码，结合量子密钥分发等量子加密技术确保数据传输安全 [3] - LSQb算法可识别关键量子比特，优化嵌入和提取过程，降低算法复杂度；量子加密技术提供无条件安全，防止信息泄露 [3] 技术流程 原始图像预处理 - 对原始图像进行压缩感知和稀疏表示，提取关键特征并转换为量子比特形式，用机器学习或深度学习模型分析，保留重要视觉元素，减少编码信息和算法复杂度 [4] 量子比特选择与嵌入 - 采用改进的LSQb算法将选定的关键量子比特嵌入量子态，引入量子纠错码和量子纠缠特性增强系统鲁棒性和稳定性，减少不必要的量子门操作 [5] 量子密钥分发与加密 - 利用量子密钥分发技术生成共享密钥，发送方和接收方交换相关量子态生成密钥，防止信息泄露 [6] 信息传输与保护 - 加密的量子态信息通过量子通道传输，结合量子隐形传态等协议增强系统安全性和灵活性 [7] 信息解密与恢复 - 接收方用共享密钥解密量子态信息，应用逆量子门操作恢复原始量子比特序列，通过解码算法提取关键特征信息并重新组装成完整图像，引入纠错机制确保高保真恢复 [8] 技术优势 - 集成LSQb算法与相关理论，结合量子加密技术构建更安全的量子信息隐藏和传输系统，减少量子资源需求，提高算法执行速度 [9] - 利用量子加密技术的无条件安全性确保数据传输的高保密性，增强信息处理效率和系统抗干扰能力，降低硬件实现成本和技术复杂度 [9] 应用领域 现有应用 - 系统已应用于医疗图像加密和金融交易系统，增强信息安全，提高处理效率 [10][11] 未来展望 - 随着量子计算和量子加密技术的发展，系统有望拓展到人工智能和大数据分析等新兴领域，加速机器学习模型训练，快速提取海量数据集中的有价值信息 [11] 公司简介 - 公司是开曼群岛豁免公司，致力于定制中央处理算法的开发和应用，通过将中央处理算法与软件或硬件集成提供全面解决方案，服务包括算法优化、加速计算能力、轻量级数据处理和数据智能服务 [12]

SHENZHEN, China, June 6, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), explored the possibilities of quantum technology in various application scenarios, particularly in the training of Quantum Neural Networks (QNNs). Quantum Neural Networks combine the advantages of quantum computing and machine learning, promising revolutionary breakthroughs in fields such as data processing and pattern recognition.Quantum Phase Estimation (QPE) is a key technique in quantum computing ...

SHENZHEN, May 27, 2025 (GLOBE NEWSWIRE) -- MicroAlgo Inc. Explores Optimization of Quantum Error Correction Algorithms to Enhance Quantum Algorithm Accuracy Shenzhen, May. 27, 2025––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced efforts to improve the accuracy and reliability of quantum algorithms by exploring and optimizing quantum error correction algorithms. Quantum error correction algorithms are designed to detect and correct errors in qubits. Due to the fragility of qubi ...

Hybrid Quantum-Classical Architecture: Combining the parallel advantages of quantum computing with the flexibility of classical computing to achieve efficient collaborative training. shenzhen, May 20, 2025 (GLOBE NEWSWIRE) -- Shenzhen, May. 20, 2025/––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), announced that quantum algorithms will be deeply integrated with machine learning to explore practical application scenarios for quantum acceleration. Quantum machine learning algorithms represent a ...

文章核心观点 - 公司宣布开发基于量子纠缠的监督量子分类器训练算法，突破传统算法能力限制，虽量子计算面临挑战但该技术在机器学习领域潜力大 [1][12] 算法介绍 - 开发新型基于量子纠缠的监督量子分类器训练算法，引入基于贝尔不等式的成本函数，可同时编码多个训练样本误差 [1] - 算法核心是利用量子纠缠构建能同时处理多个训练样本及其标签的模型，可并行处理多个样本，提升训练效率 [2] - 用量子叠加将训练样本表示为量子比特向量，通过量子门操作将标签信息编码到量子态，利用纠缠关系同时处理多个样本 [3] - 基于贝尔不等式的成本函数可同时编码多个样本分类误差，优化过程考虑多个样本集体性能，克服传统算法局部优化问题 [4] 算法实现 - 依赖量子计算技术的量子比特、量子门操作和量子测量等核心组件处理输入数据 [5] - 算法初始阶段将输入训练样本转换为量子比特并初始化为特定量子态，对多个量子比特进行纠缠操作 [6] - 训练样本被安排成纠缠态，通过纠缠共享和处理信息，提高数据处理效率并加速训练收敛 [7] - 利用贝尔不等式构建成本函数以最小化分类误差，通过量子算法计算有效最小化成本函数 [8] - 算法通过量子测量输出分类结果，量子计算并行处理能力可在短时间内完成复杂分类任务 [8] 技术优势 - 利用量子纠缠特性并行处理多个训练样本，加速训练速度并提高分类准确率，可克服传统方法处理大数据集的计算瓶颈 [9] - 基于贝尔不等式的成本函数理论上更稳健，可避免传统方法的局部最优问题，在复杂分类任务中更有效 [10] 面临挑战 - 量子计算面临稳定性和计算规模等限制，量子比特数量和误差率影响算法实际性能，在现有平台实现高效算法需突破技术障碍 [11] 公司概况 - 公司致力于定制中央处理算法的开发和应用，通过将算法与软硬件结合为客户提供综合解决方案 [13] - 服务包括算法优化、加速计算能力、轻量级数据处理和数据智能服务等，高效交付软硬件优化是长期发展动力 [13]

Shenzhen, May 14, 2025 (GLOBE NEWSWIRE) -- MicroAlgo Inc. Announces Research on Quantum Information Recursive Optimization (QIRO) Algorithm, for Combinatorial Optimization Problems to Expand and Solve New Ideas Shenzhen, May. 14, 2025––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced the research of the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to provide a new approach to combinatorial optimization problems by leveraging the power of quantum comput ...

SHENZHEN, China, May 12, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), they announced today their research on quantum visual computing, exploring the integration of quantum computing with classical convolutional neural networks. They are developing a Quantum Convolutional Neural Network (QCNN) architecture to enhance the performance of traditional computer vision tasks using quantum mechanics principles.The Quantum Convolutional Neural Network (QCNN) architecture is an i ...

SHENZHEN, China, May 8, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO) announced that the quantum image encryption algorithm they developed, based on quantum key images, is an innovative image protection scheme. This algorithm uses a quantum key image to store encryption keys, leveraging quantum entanglement and parallelism to achieve efficient image encryption. The quantum key image is a special type of quantum image prepared using a specific quantum storage method, with ...

SHENZHEN, May 08, 2025 (GLOBE NEWSWIRE) -- MicroAlgo Inc. Develops a Blockchain Storage Optimization Solution Based on the Archimedes Optimization Algorithm (AOA) Shenzhen, May. 08, 2025/––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), announced a focus on addressing the efficiency bottlenecks in blockchain storage by introducing the Archimedes Optimization Algorithm (AOA) into distributed storage architecture. Through intelligent algorithmic restructuring of data storage and node collaborati ...