Rail Vision and Quantum Transportation Unveil First Transformer-Based Neural Decoder for Universal Quantum Error Correction

Rail Vision Ltd. (NASDAQ: RVSN), an early-stage technology company focused on revolutionizing railway safety and data‑driven markets, announced that its majority‑owned subsidiary, Quantum Transportation Ltd., has developed and validated a prototype transformer‑based neural decoder designed for universal quantum error correction (QEC). This breakthrough represents the first of its kind — a code‑agnostic, machine‑learning driven decoder capable of handling a wide variety of quantum error correction codes and outperforming leading classical decoding algorithms like Minimum‑Weight Perfect Matching and Union‑Find in simulation tests. The new decoder uses advanced transformer architecture optimized for the complex, high‑dimensional nature of quantum error syndromes, showing superior accuracy and efficiency across multiple code distances, noise profiles, and error rates. The project also includes a comprehensive intellectual property strategy to support this transformative approach. While initially aimed at quantum computing research, Rail Vision and Quantum Transportation are exploring future applications of the underlying technologies in Rail Vision’s core systems. David BenDavid, CEO of Rail Vision, emphasized the importance of this breakthrough in highlighting Quantum Transportation’s research strength and long‑term potential. #QuantumErrorCorrection #QuantumComputing #AI #MachineLearning #SlimScan #GrowthStocks #CANSLIM