Core Idea - WiMi Hologram Cloud Inc. has introduced a new Lean Classical-Quantum Hybrid Neural Network (LCQHNN) framework designed to enhance learning efficiency while minimizing quantum circuit complexity, marking a significant advancement in the practical application of quantum neural networks [1][11]. Technical Overview - The LCQHNN framework focuses on quantum feature amplification combined with classical stability optimization, creating an efficient interaction mechanism between classical and quantum computing [2]. - The architecture consists of a Classical Front-End for feature extraction and a Quantum Back-End utilizing variational quantum circuits for classification [2]. - The classical component employs lightweight convolutional layers for data preprocessing, embedding results into quantum state space for feature transformation [3]. - The quantum section features a four-layer variational quantum circuit (4-layer VQC) that optimizes circuit parameters to enhance classification performance while reducing resource consumption [4]. Workflow Stages - The workflow includes several key stages: 1. Data Preprocessing and Classical Encoding, where images are processed into medium-dimensional vectors for quantum encoding [5]. 2. Quantum State Preparation and Entanglement Structure Construction, enhancing correlations between qubits to improve model performance [6]. 3. Parameterized Quantum Evolution and Measurable Readout, utilizing adjustable parameters for efficient training and measurement [7]. 4. Classical Feedback and Hybrid Optimization, coordinating classical and quantum parameter updates to minimize classification errors [8]. 5. Classification Decision and Feature Visualization, where final results are decoded back to the classical domain, demonstrating strong inter-class separability [9]. Future Directions - WiMi plans to expand the LCQHNN model into multimodal learning, integrate with quantum support vector machines and quantum convolutional networks, and promote prototype deployment on quantum hardware to validate performance in real-world scenarios [10]. - The company aims to combine quantum parallel optimization with federated learning frameworks to develop secure and efficient quantum intelligent systems [10]. Company Background - WiMi Hologram Cloud Inc. specializes in holographic cloud services, focusing on various professional applications including AR technologies, holographic devices, and metaverse solutions [12].