Synergy of Quantum Computing, Artificial Intelligence, and Brain-Computer Interfaces for Practical Radio Communication, Radar, and Navigation Tasks via Quantum Parallelism Using IBM Q and GPT Chat

Abstract In recent years, quantum computing (QC) and artificial intelligence (AI) have achieved breakthroughs across various scientific and engineering domains, including radio communication, radar, and navigation systems. These applications involve complex computations, high precision requirements, and robustness against noise—challenges that can benefit from the combined power of quantum computing and AI. This study explores the synergistic potential of QC, AI, and brain-computer interfaces (BCIs) to address practical transport and navigation tasks using quantum parallelism. By leveraging IBM Q for quantum computation and GPT Chat for AI-assisted modeling, the research demonstrates methods for optimizing signal processing, error mitigation, and decision-making in radio-based systems. The integration of these technologies enables: Efficient simulation and processing of high-dimensional data in real time. Enhanced robustness to interference and environmental noise. Adaptive algorithms guided by AI insights for optimal performance. This approach highlights the practical applicability of hybrid quantum-classical systems in transport and navigation, paving the way for next-generation solutions that combine quantum computational speed, AI intelligence, and human-computer interfacing.