MicroAlgo (MLGO) Stock News

MicroAlgo (NASDAQ: MLGO) announced a multi-objective evolutionary algorithm that automatically designs quantum circuits from scratch using a task-universal component library.

The tool simultaneously optimizes metrics such as accuracy, width, depth, and gate count, and has been validated on classic quantum algorithms including Quantum Fourier Transform and Grover's Search.

MicroAlgo (NASDAQ: MLGO) on May 8, 2026 announced Quantum Architecture Search (QAS), an automated method to optimize quantum circuit architectures for variational quantum algorithms (VQA).

QAS uses reinforcement learning, genetic algorithms and noise modeling to improve VQA trainability, avoid barren plateaus, and reportedly speeds training >40% while boosting robustness in noisy environments by 30%.

MicroAlgo (NASDAQ: MLGO) announced a quantum blockchain architecture using cyclic quantum secure channels (QSC) and quantum key distribution (QKD) to enhance transaction security and transparency. The design uses four layers: quantum communication, blockchain core, smart contract, and application.

QKD secures key generation/distribution, quantum encryption protects transaction data, and periodic key rotation plus quantum signatures aim to support real-time verification while preserving decentralization. Company notes commercialization and scalability of quantum components remain challenges for large-scale deployment.

MicroAlgo (NASDAQ: MLGO) on April 30, 2026 announced a new technical framework for designing optimal exact quantum query algorithms built from the sum-of-squares representation form of Boolean functions. The three-step approach covers SOS representation, construction of final quantum states, and selection of unitary operators.

The company says the method offers theoretical advances and potential practical applications in quantum decision trees, quantum communication, security, and quantum machine learning, while noting feasibility limits for some practical cases.

MicroAlgo (NASDAQ: MLGO) announced development of quantum algorithms for feedforward neural networks on April 24, 2026. The technology introduces approximate quantum inner-product subroutines, uses QRAM for intermediate-value storage, and claims linear training-time complexity and natural resistance to overfitting, while noting hardware and portability challenges.

MicroAlgo (NASDAQ: MLGO) reported full-year 2025 results for the year ended December 31, 2025, with net profit of RMB 127.56 million (USD 18.15 million), up 143.5% year‑over‑year. Diluted EPS rose to RMB 14.87 (USD 2.12), a 272.7% increase.

2025 operating revenue was RMB 422.05 million (USD 60.05 million), gross profit RMB 108.82 million and gross margin 25.8%. Total shareholders' equity reached RMB 2,321.80 million (USD 330.33 million), up 122.8%. Operating expenses fell 35.3%, and operating profit was RMB 22.38 million, up 11.1%.

MicroAlgo Inc. (NASDAQ: MLGO) has announced the development of a breakthrough Grover-based quantum algorithm for finding pure Nash equilibria in graphical games. The technology leverages quantum computing's amplitude amplification techniques to identify solutions with square-root complexity, making it significantly more efficient than traditional methods.

The company's innovative approach transforms game theory problems into Boolean satisfiability equations, mapping them onto quantum circuits. Through extensive testing using quantum simulators, MicroAlgo's algorithm has demonstrated superior performance in speed and accuracy compared to conventional methods, particularly in complex gaming environments.

MicroAlgo Inc. (NASDAQ: MLGO) has announced the integration of quantum image LSQb (Least Significant Quantum Bit) algorithm with quantum encryption technology to create an advanced information hiding and transmission system. The system combines LSQb algorithm for efficient information encoding/decoding with Quantum Key Distribution (QKD) for secure data transmission. The technology processes images through steps including preprocessing, quantum bit selection, encryption, transmission, and recovery. Key innovations include compressed sensing, sparse representation, and quantum error correction. The system has been implemented in medical image encryption and financial transaction systems, demonstrating practical applications in protecting sensitive data. The technology reduces quantum resources usage, minimizes quantum gate operations, and ensures high information fidelity while maintaining security.

MicroAlgo Inc. (NASDAQ: MLGO) has announced the adoption of Quantum Phase Estimation (QPE) method to enhance its Quantum Neural Network (QNN) training capabilities. The company has implemented a comprehensive quantum circuit construction process that includes state initialization, controlled unitary operations, and inverse Quantum Fourier Transform application. The technology leverages quantum computing's parallelism to accelerate neural network training, particularly benefiting image processing and natural language processing applications. The QPE method enables more efficient parameter optimization, improved training stability through error correction, and enhanced processing speed and accuracy compared to traditional methods. This advancement positions MicroAlgo to better handle large-scale image datasets and natural language processing tasks like machine translation and text classification.