MicroCloud Hologram Inc. Utilizes Matrix Product States to Achieve High-Precision Quantum State Preparation with Mirror-Symmetric Probability Distribution

Core Viewpoint - MicroCloud Hologram Inc. has proposed a new method based on Matrix Product States (MPS) that significantly enhances quantum state preparation accuracy and computational efficiency, achieving improvements by two orders of magnitude [1][12]. Group 1: Technology Overview - The new method utilizes a shallow quantum circuit design primarily composed of nearest-neighbor qubit gates, which enhances feasibility on current noisy quantum devices [2][6]. - The research indicates that approximation accuracy in tensor networks is mainly dependent on bond dimension rather than the number of qubits, facilitating future large-scale adoption [2][12]. - The method optimizes the loading of probability distributions by leveraging mirror symmetry, which reduces entanglement and improves computational efficiency [4][5]. Group 2: Advantages of the New Method - The proposed method achieves a precision improvement of two orders of magnitude compared to existing MPS techniques while significantly reducing computation time [8][12]. - The optimized shallow quantum circuit design minimizes global gate operations, reducing circuit depth and enhancing computational stability [6][7]. - The linear scalability of the method allows it to adapt to larger-scale quantum systems without a corresponding exponential increase in computational complexity [7][10]. Group 3: Applications and Future Directions - The MPS method is particularly suitable for high-dimensional probability distributions, making it ideal for applications in quantum finance and quantum machine learning [10][12]. - Future research will focus on optimizing computational complexity, improving adaptability across different quantum hardware platforms, and exploring additional application areas [13].