Enhanced Simulation of Urban Systems Using Quantum Digital Twins

Simulation of urban systems faces challenges in accuracy and computational time due to dynamics, large-scale data, and interdependencies among subsystems (energy, transportation, waste, public services). The “digital twin,” as a virtual representation synchronized with the physical world, is considered a key tool for smart city management by enabling data exchange and near-real-time simulation scenario execution. However, the limitations of classical computing in solving optimization problems and complex simulations have strengthened the motivation to move toward “quantum digital twins.” In this paper, drawing on the presented literature, we review the theoretical foundations of digital twins and quantum computing, research advances in quantum-computing-based digital twins, and their applications for improving simulation of urban systems. We then propose a framework for synergizing IoT data, digital twin models, and quantum/hybrid algorithms. The conclusion indicates that quantum digital twins can increase prediction accuracy, optimization capability, and resilience of urban decision-making, but challenges such as noise and errors in quantum hardware, scalability, data governance, and post-quantum security remain decisive.

کلیدواژه ها:

Digital twin ، quantum digital twin ، smart city ، quantum simulation ، energy optimization ، traffic management ، post-quantum security ، data governance