MicroCloud Hologram Inc. Proposes Quantum AI Simulator Adopting Hybrid CPU-FPGA Method, Achieving Efficient Image Classification Simulation Through Heterogeneous Computing

SHENZHEN, China, Feb. 26, 2026 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs hardware-level optimization on the specific structure of quantum kernels through a heterogeneous computing architecture, making quantum kernel estimation 500 times faster than traditional CPU simulation implementations under the same computational scale, providing unprecedented acceleration capabilities for the application simulation of quantum artificial intelligence.

This technology of HOLO focuses on application-specific quantum kernels (ASQK) designed for image classification tasks, and for the first time implements its core computational process on a Field Programmable Gate Array (FPGA). Through deep collaborative design of quantum kernel structures, feature encoding methods, and FPGA dataflow architectures, HOLO has constructed a hardware acceleration platform oriented towards quantum machine learning algorithms, enabling the simulation of quantum kernel models with high-dimensional feature encoding capabilities under classical computing resources. This achievement not only breaks through the physical qubit limitations faced by current noisy intermediate-scale quantum (NISQ) devices but also provides a new direction for future hardware-based quantum algorithm prototype verification.

In terms of the specific construction of the quantum kernel, HOLO designed an empirical parameterized encoding strategy for image classification tasks. Image samples are first compressed into fixed-dimensional feature vectors, and then transformed into rotation angle parameters via nonlinear mapping to input into the quantum circuit. The quantum kernel circuit structure includes multiple layers of controlled rotation gates and entanglement gates, used to construct global feature correlations. Through experimental comparisons, it is obtained that appropriately increasing the quantum kernel depth can significantly improve classification performance, but it also leads to exponential growth in simulation complexity. Therefore, HOLO adopted a collaborative optimization strategy, namely restricting the entanglement range of the circuit at the algorithm level, while at the hardware level performing logic reuse and lookup table optimization on common gate operations (such as RY, CNOT, CZ, etc.) to maximize hardware utilization. On this basis, the FPGA's logic resource utilization rate is maintained below 82%, and the on-chip storage bandwidth can support quantum state update operations for 256 parallel channels.

To further verify the performance of the simulator, HOLO conducted tests on the system across multiple sets of image classification tasks, including the classic MNIST and Fashion-MNIST datasets. The experimental results indicate that the FPGA-accelerated quantum kernel estimation, under the same sample scale, has a runtime of only about 1/500 of the CPU implementation, and achieves classification accuracy comparable to the Gaussian kernel (RBF Kernel) with optimized hyperparameters. This means that, through reasonably designed quantum kernel structures and efficient hardware acceleration mechanisms, HOLO can reproduce the core performance characteristics of quantum algorithms on classical hardware without relying on actual quantum hardware. More importantly, this simulation platform provides a practical and feasible channel for algorithm verification, model comparison, and scalability testing of quantum machine learning algorithms.

In future research plans, HOLO will further expand the functions of this simulator, including support for more complex quantum circuit structures, more general quantum kernel types, and automated circuit-to-hardware mapping compilers. By combining FPGA acceleration units with GPUs or quantum simulation cloud platforms, it hopes to achieve multi-node quantum simulation clusters to support hybrid state evolution and noise modeling for hundreds of qubits. At the same time, HOLO also plans to explore quantum-classical collaborative training mechanisms based on this framework, enabling quantum kernels to adaptively adjust encoding structures during the training process, thereby achieving true quantum neural network simulation.

The hybrid CPU-FPGA quantum AI simulator proposed by HOLO is not only a hardware optimization project but also an innovation in computational paradigms. It combines the programmability of classical hardware with the high-dimensional mapping capabilities of quantum algorithms, providing new tools for quantum machine learning research and laying the technical foundation for the design of next-generation quantum accelerators. In the future, with the continuous expansion of FPGA scales and the in-depth development of quantum algorithms, such heterogeneous quantum simulation systems are expected to become important supporting platforms for quantum artificial intelligence research, accelerating the transition from algorithm prototypes to actual quantum applications, and driving quantum computing from experimental exploration toward a new stage of engineering and industrialization.

About MicroCloud Hologram Inc.

MicroCloud Hologram Inc. (NASDAQ: HOLO) is committed to the research and development and application of holographic technology. Its holographic technology services include holographic light detection and ranging (LiDAR) solutions based on holographic technology, holographic LiDAR point cloud algorithm architecture design, technical holographic imaging solutions, holographic LiDAR sensor chip design, and holographic vehicle intelligent vision technology, providing services to customers offering holographic advanced driving assistance systems (ADAS). MicroCloud Hologram Inc. provides holographic technology services to global customers. MicroCloud Hologram Inc. also provides holographic digital twin technology services and owns proprietary holographic digital twin technology resource libraries. Its holographic digital twin technology resource library utilizes a combination of holographic digital twin software, digital content, space data-driven data science, holographic digital cloud algorithms, and holographic 3D capture technology to capture shapes and objects in 3D holographic form. MicroCloud Hologram Inc. focuses on developments such as quantum computing and quantum holography, with cash reserves exceeding 3 billion RMB, and plans to invest more than 400 million in USD from the cash reserves to engage in blockchain development, quantum computing technology development, quantum holography technology development, and derivatives and technology development in frontier technology fields such as artificial intelligence AR. MicroCloud Hologram Inc.'s goal is to become a global leading quantum holography and quantum computing technology company.

Safe Harbor Statement

This press release contains forward-looking statements as defined by the Private Securities Litigation Reform Act of 1995. Forward-looking statements include statements concerning plans, objectives, goals, strategies, future events or performance, and underlying assumptions and other statements that are other than statements of historical facts. When the Company uses words such as "may," "will," "intend," "should," "believe," "expect," "anticipate," "project," "estimate," or similar expressions that do not relate solely to historical matters, it is making forward-looking statements. Forward-looking statements are not guarantees of future performance and involve risks and uncertainties that may cause the actual results to differ materially from the Company's expectations discussed in the forward-looking statements. These statements are subject to uncertainties and risks including, but not limited to, the following: the Company's goals and strategies; the Company's future business development; product and service demand and acceptance; changes in technology; economic conditions; reputation and brand; the impact of competition and pricing; government regulations; fluctuations in general economic; financial condition and results of operations; the expected growth of the holographic industry and business conditions in China and the international markets the Company plans to serve and assumptions underlying or related to any of the foregoing and other risks contained in reports filed by the Company with the Securities and Exchange Commission ("SEC"), including the Company's most recently filed Annual Report on Form 10-K and current report on Form 6-K and its subsequent filings. For these reasons, among others, investors are cautioned not to place undue reliance upon any forward-looking statements in this press release. Additional factors are discussed in the Company's filings with the SEC, which are available for review at www.sec.gov. The Company undertakes no obligation to publicly revise these forward-looking statements to reflect events or circumstances that arise after the date hereof.

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