Accessibility StatementSkip Navigation SHENZHEN, China, Nov. 20, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively proposed the "quantum degree" concept, establishing a brand-new theoretical framework for the research on synchronization characteristics of quantum systems. This technology, by introducing the concept of quantum degree in quantum synchronization, precisely measures the synchronized quantum properties in quantum ...

Core Viewpoint - MicroCloud Hologram Inc. has launched a multi-class classification method based on Quantum Convolutional Neural Network (QCNN) using hybrid quantum-classical learning, showcasing the potential of quantum computing in artificial intelligence and addressing limitations of traditional computing architectures [1][12]. Technology Development - The new technology addresses bottlenecks in classical neural networks, particularly in computing power, energy consumption, and model complexity, as data scales and classification categories expand [2][10]. - The core of the technology is a multi-class classification model that integrates quantum convolutional neural networks with a hybrid quantum-classical optimization framework, utilizing the TensorFlow Quantum platform [3][9]. Model Design - HOLO introduced a quantum perceptron model that leverages quantum state evolution and measurement, enhancing feature extraction through quantum gates, which allows for high-dimensional feature mappings [4][9]. - The model optimizes circuit complexity and improves expressive power by reducing redundant gate operations and enhancing entanglement structures [4][9]. Training Mechanism - The hybrid quantum-classical learning mechanism significantly improves training efficiency and model convergence speed by combining quantum state encoding with classical optimization algorithms [5][12]. - The training process involves quantum circuits encoding input samples, producing measurement results that are normalized and used to update quantum circuit parameters iteratively [5][8]. Experimental Results - Experimental results indicate that HOLO's quantum convolutional neural network achieves accuracy comparable to classical convolutional networks in four-class classification tasks, validating the feasibility of quantum neural networks for practical applications [6][12]. Industry Context - The technology is positioned to address challenges in various fields such as computer vision, medical image analysis, and natural language processing, where traditional deep learning methods face limitations due to high energy consumption and long training times [10][12]. - HOLO's quantum convolutional neural network method aims to reduce computational complexity and leverage future advancements in quantum hardware for significant breakthroughs in computing power [10][11]. Future Prospects - The technology lays the groundwork for broader applications of quantum machine learning, with expectations for expansion into large-scale image recognition and real-time video processing as quantum hardware advances [11][12]. - HOLO plans to further optimize quantum circuits and explore multi-layer quantum convolutional networks combined with deep residual structures in future research [11].

Group 1: Company Overview - Mengyun Holography (HOLO.US) expects to achieve a net profit exceeding RMB 350 million for the year 2025, a significant turnaround from a net loss in the previous year [1] - The company reported a net loss of approximately RMB 63 million for the entire year of 2024 [1] - Mengyun Holography currently holds over RMB 3 billion in cash, cash equivalents, and short-term investments [1] - The company plans to allocate over $400 million from its cash reserves to invest in quantum computing, blockchain, and quantum holography technologies [1] Group 2: Industry Trends - The quantum computing sector in the U.S. stock market has seen a strong performance, with Mengyun Holography experiencing a pre-market surge of over 17% following positive news [2] - Recent developments, including the U.S. government's consideration of using federal funds to acquire equity in quantum computing companies, have led to a collective rise in quantum sector stocks [2] - Key players in the quantum computing field, such as IonQ, Rigetti, and D-Wave, have also seen significant stock price increases, reinforcing expectations of a "national-level track" premium [2] - Industry experts believe that the quantum computing field is approaching critical milestones, with the potential for achieving "quantum advantage" and "quantum supremacy" within the next three to five years [2][3] - IonQ's CEO has indicated that the era of "quantum supremacy" is imminent, marking a significant threshold where quantum processors can outperform classical supercomputers on specific tasks [3] - Quantum computing systems leverage quantum mechanics properties, such as superposition and entanglement, to provide a new computing paradigm that could vastly exceed traditional binary computers in certain areas [3]

Core Insights - MicroCloud Hologram Inc. anticipates achieving significant profitability in 2025, projecting a net income exceeding RMB 350 million, a substantial improvement from a net loss of approximately RMB 63 million in 2024 [1][2]. Financial Performance - The company expects a positive contribution to its cash position for the full year 2025 due to the projected net income [2]. - As of now, MicroCloud Hologram Inc. holds cash, cash equivalents, and short-term investments totaling over RMB 3 billion [3]. Investment Strategy - The company plans to deploy over US$400 million from its cash reserves to invest aggressively in quantum computing, blockchain, and quantum holography technologies [3][4]. - The goal is to establish a leading position in the quantum computing and quantum holography sectors [3][4]. Technology Focus - MicroCloud Hologram Inc. is committed to the research and development of holographic technology, including services such as holographic LiDAR solutions and holographic digital twin technology [4]. - The company aims to become a global leader in quantum holography and quantum computing technology [4].

Core Insights - MicroCloud Hologram Inc. has proposed a Quantum Convolutional Neural Network (QCNN) that utilizes hybrid quantum-classical learning, achieving accuracy comparable to classical Convolutional Neural Networks (CNNs) on the MNIST dataset, indicating the practical feasibility of quantum computing in machine learning tasks [1][3][12] Company Overview - MicroCloud Hologram Inc. focuses on providing advanced holographic technology services, including high-precision holographic LiDAR solutions and holographic digital twin technology [15] - The company plans to invest over $400 million in cutting-edge technology sectors, including quantum computing, quantum holography, and artificial intelligence [15] Technological Innovation - The proposed QCNN leverages a hybrid quantum-classical learning framework, combining classical optimizers with quantum circuits to enhance feature extraction and classification tasks [4][11] - The architecture includes a novel Quantum Perceptron model that improves feature extraction and nonlinear mapping capabilities [11] - The quantum circuit employs eight qubits for data encoding and four auxiliary qubits to enhance expressive power, effectively mapping input data for classification [5][11] Application Potential - The QCNN can be applied to various complex datasets and tasks, such as multi-class traffic sign recognition in autonomous driving and multi-class classification of lesions in medical imaging [12][13] - The integration of quantum computing with classical learning offers significant advantages in energy efficiency, parameter efficiency, and computational acceleration for enterprises [13]

Core Viewpoint - MicroCloud Hologram Inc. has proposed an advanced quantum Grover algorithm that enhances dynamic multi-mode search capabilities on reconfigurable hardware, achieving significant theoretical and practical advancements in quantum computing [1][14]. Technical Innovations - The new dynamic multi-mode Grover search algorithm allows for flexible switching between multiple target modes, overcoming the limitations of traditional single-target searches [2][14]. - The introduction of dynamically variable phase control logic at the orchestration level of the quantum circuit enhances application flexibility and search efficiency [3][14]. - The redesigned circuit architecture simplifies the traditional Grover algorithm's four stages, reducing resource waste and execution delays associated with multi-target searches [4][14]. - A configurable lookup table (CLUT) enables dynamic phase modulation in the oracle design, allowing for runtime target modifications without circuit recompilation [5][14]. - The diffusion operator design employs a hierarchical control method for qubits, ensuring efficient searches under multi-mode conditions by reducing circuit redundancy [6][14]. - Hardware-level entanglement optimization strategies balance entanglement operations and wiring overhead, effectively reducing circuit latency and power consumption [7][14]. Hardware Implementation - High-performance Field Programmable Gate Arrays (FPGAs) are utilized for their reconfigurable characteristics, supporting the simulation and verification of quantum algorithms [8][14]. - The quantum state register array supports parallel storage and updates for up to 22 qubits, enhancing concurrency in quantum gate operations [9][14]. - The quantum gate control logic allows for dynamic rearrangement of quantum gate operations, facilitating multi-mode adjustments at the hardware level [10][14]. - The oracle-diffusion joint execution module merges oracle and diffusion operations, improving throughput and simulation speed through pipelinable characteristics [11][14]. - Monitoring and optimization of FPGA resource utilization have led to stable operation of 22-qubit circuits, surpassing previous simulation records [12][14]. Industry Implications - The dynamic multi-mode Grover search algorithm presents a new acceleration path for high-performance search tasks, applicable in fields such as cryptanalysis, pattern recognition, and quantum database retrieval [14]. - This technology marks a significant milestone in transitioning quantum computing from theoretical algorithms to practical systems, with potential for broader applications as research progresses [14].

Core Viewpoint - MicroCloud Hologram Inc. has proposed a quantum secure tripartite computing protocol based on Blind Quantum Computing (BQC), addressing data privacy concerns in multi-client collaborative computing [1][2][4]. Group 1: Quantum Secure Tripartite Computing Protocol - The proposed protocol involves two quantum-limited clients and a remote quantum server, ensuring that the server cannot access the specific content of the clients' data during computation [1][2]. - This approach allows mutually distrusting clients to engage in collaborative computing without the risk of data privacy leakage [2][3]. Group 2: Extension to Multi-Party Computing - HOLO has expanded the tripartite protocol into a quantum secure multi-party computing protocol, which supports more than two clients while maintaining independent privacy protection for each client's data [3][4]. - The protocol systematically adjusts data transmission paths and server processing workflows to ensure security and efficiency in multi-client scenarios [3][4]. Group 3: Future Implications and Investments - The multi-party computing protocol lays the groundwork for broader applications of quantum computing, with potential for further optimization as quantum technology advances [4]. - MicroCloud plans to invest over $400 million in various cutting-edge technology sectors, including quantum computing and blockchain development [5].

Core Insights - MicroCloud Hologram Inc. proposes a feasible path for achieving computational advantages in quantum computing through collaborative utilization of QPUs, error control, and algorithm optimization [1][2]. Quantum Computing Strategy - The company emphasizes the importance of circuit knitting technology to combine multiple QPUs, allowing for larger-scale quantum computing tasks by distributing complex quantum circuits into sub-circuits for parallel processing [2]. - Error suppression and mitigation techniques are highlighted as essential for reducing the impact of errors on computational results, enhancing the quality of solutions through optimized quantum gate operations and classical post-processing [2]. - The focus on heuristic quantum algorithms with asymptotic speedup aims to provide efficient solutions to practical problems, making them suitable for immediate applications despite not guaranteeing optimal solutions [2]. Quantum-Centric Supercomputing Architecture - MicroCloud proposes a "quantum-centric supercomputing" architecture that integrates quantum and classical processors, redefining their relationship to enhance computational efficiency [3]. - This architecture assigns tasks based on the characteristics of computing tasks, facilitating a collaborative working mode between quantum and classical processors [3]. Future Development and User Experience - The company acknowledges the increasing complexity of quantum computing systems and the need for higher levels of automation and intelligence in quantum software to simplify user interaction [4]. - The proposed "frictionless" user experience aims to lower the application threshold for quantum computing, promoting its adoption across various fields such as finance and healthcare [4]. Investment and Technology Focus - MicroCloud is committed to investing over $400 million in cutting-edge technology sectors, including quantum computing, quantum holography, and artificial intelligence [6].

Core Insights - MicroCloud Hologram Inc. has proposed a novel quantum computing method that utilizes a universal "quantum variable" form, enhancing flexibility and breaking the limitations of traditional quantum computing [1][4] - The company has developed a specific implementation model for universal quantum computing, relying on three core elements: a fixed two-body auxiliary-register interaction gate, auxiliaries in a single state, and local measurements [2][4] - The proposed quantum computing model combines the advantages of hybrid quantum-classical processing, allowing for efficient handling of complex quantum state operations while maintaining control and data processing through classical computing [3][4] Quantum Computing Method - The new quantum computing method allows for the use of various types of quantum variables, including traditional qubits and high-dimensional qubits, significantly expanding its application range [1][4] - The auxiliary plays a crucial role in mediating gate operations on quantum memory registers, enabling control without interfering with the core quantum state [1][4] Implementation Model - The implementation model simplifies the quantum computing process by using a single fixed gate, which reduces system complexity and enhances operational efficiency [2][4] - Consistent initial states for auxiliaries minimize computational errors, while local measurements facilitate the regulation of the computation process [2][4] Hybrid Processing Advantages - The model offers hybrid quantum-classical processing benefits, merging the strengths of quantum computing's parallelism with the control and flexibility of classical computing [3][4] - This approach is expected to support the development of more efficient and practical quantum computing systems, particularly in high-dimensional quantum information processing and complex simulations [4] Company Overview - MicroCloud Hologram Inc. focuses on providing advanced holographic technology services, including LiDAR solutions and holographic imaging technologies [6][7] - The company plans to invest over $400 million in various cutting-edge technology sectors, including quantum computing and blockchain development [7]

Core Insights - MicroCloud Hologram Inc. has conducted research on optimizing quantum channel implementation, focusing on minimizing C-NOT gate counts while ensuring functional correctness [1][3][7] - The company has developed three quantum circuit models: Quantum Circuit Model (QCM), RandomQCM, and MeasuredQCM, each providing different degrees of freedom for circuit design [2][4][5] Quantum Circuit Models - The Quantum Circuit Model (QCM) utilizes a strict sequence of single-qubit and C-NOT gates, ensuring deterministic implementation but with limited operational freedom [2] - RandomQCM introduces classical randomness to allow probabilistic operations, which helps in reducing C-NOT gate counts, especially for probabilistic quantum channels [2][4] - MeasuredQCM incorporates measurement operations and conditional control, enhancing circuit flexibility and enabling simplified decomposition of complex quantum channels [2][4][5] C-NOT Gate Optimization - The research establishes lower bounds on C-NOT gate counts for quantum channel decomposition, influenced by the channel's entanglement capacity and qubit dimensions [3][4] - Near-optimal solutions were found, with C-NOT gate counts controlled within 1.5 times the theoretical lower bound in QCM, 1.2 times in RandomQCM, and approaching the lower bound in MeasuredQCM [4][5] Practical Applications and Challenges - The research provides a new paradigm for quantum circuit design that integrates measurement, classical feedback, and quantum operations, enhancing resource efficiency [5] - Challenges remain in practical applications, such as the need for precise control of measurement timing and high real-time performance from classical control logic [6] Company Overview - MicroCloud Hologram Inc. focuses on holographic technology services, including LiDAR solutions and holographic digital twin technology, and plans to invest over $400 million in quantum computing and related technologies [8][9]