WiMi proposes a quantum AI system built around three-qubit interactions and plans real-device tests

BEIJING, Aug. 21, 2026 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, proposes a cutting-edge quantum machine learning technology oriented toward classical data classification tasks—a quantum convolutional neural network with interaction layers for classical data classification. This technology systematically enhances the overall performance of quantum convolutional neural networks in terms of expressive power, entanglement generation capability, and actual classification performance by introducing a novel interaction layer structure based on three-qubit interactions, marking an important step forward in the structural design of quantum deep learning models toward a new phase driven by multi-body interactions.

From the perspective of technical implementation logic, this quantum convolutional network adopts an overall hybrid quantum-classical architecture design. First, classical data is mapped to the quantum state space through an efficient data encoding strategy, ensuring that as much discriminative information from the original data as possible is preserved under limited qubit resources. For image data, the network employs block partitioning and local mapping approaches to embed pixel information into corresponding quantum subsystems; for one-dimensional data, a combination of structured amplitude encoding and angle encoding is used to achieve a compact representation of data features. After data encoding is completed, the quantum state is fed into the quantum feature extraction module composed of multiple layers of quantum convolutional units and interaction layers.