WiMi Unveils Quantum Algorithm to Compress High-Dimensional Data Without Feature Loss
Beijing – – September 11, 2026 -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) has developed a multi-dimensional data pooling technique built on Variational Quantum Algorithms (VQA) that compresses complex datasets while retaining local feature detail, a persistent bottleneck in classical machine learning pipelines.
WiMi combines Quantum Haar Transform with partial measurement to eliminate flattening losses
The scheme merges a Quantum Haar Transform (QHT) with quantum partial measurement to build what the company calls a quantum pooling mechanism. Unlike classical pooling, which compresses data by discarding information through flattening, WiMi's method operates directly on multi-dimensional data in quantum state space, avoiding the need to reduce inputs to one-dimensional form before processing.