MicroCloud Hologram announced a new learnable quantum spectral filter that maps the graph Laplacian operator to a trainable quantum circuit, enabling exponential compression of high‑dimensional graph signals into a log‑N‑dimensional feature space while using only about 20 qubits for a million‑node graph.
The filter fuses graph convolution and pooling into a single quantum process, producing a probability distribution that directly represents compressed graph features. This design reduces qubit requirements compared to classical spectral methods, positioning HOLO as a potential leader in quantum‑enhanced machine learning for large‑scale network data.
The launch extends HOLO’s quantum‑AI portfolio beyond earlier quantum convolutional neural network and quantum synchronization products. Management emphasized that building quantum frontier algorithm infrastructure now is critical, as the company aims to become a global leader in quantum holography and quantum computing. The new filter aligns with the company’s pivot from holographic hardware to quantum‑driven AI solutions.
The technology opens revenue opportunities in sectors that rely on graph analytics, such as social network analysis, traffic flow optimization, and cybersecurity. While the product is still in early stages, the company’s cash reserves exceed 3 billion RMB and it plans to invest over $400 million USD in quantum research, indicating strong financial backing for scaling the technology. In the first half of 2025, HOLO reported a net profit of RMB 238.1 million (US$33.1 million), reflecting a turnaround from prior losses and providing a solid foundation for future growth.
The quantum‑AI space is crowded, with competitors developing quantum neural networks and quantum‑enhanced deep learning tools. Investors have responded positively to HOLO’s recent quantum announcements, noting the company’s ability to deliver new products that reduce qubit requirements and accelerate algorithmic performance. The launch of the Q‑DPC Accelerator earlier in January saw a modest positive reaction, suggesting that the market values HOLO’s continued innovation in quantum‑enhanced analytics.
HOLO’s leadership believes that the learnable quantum spectral filter will accelerate adoption of quantum‑enhanced graph analytics across enterprise and government customers. The company plans to integrate the filter into its existing quantum platform and to pursue partnerships with cloud providers and data‑center operators to commercialize the technology. Management remains confident that the company’s investment in quantum infrastructure will pay off as quantum hardware matures.
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