Quantum computing-artificial intelligence synergy for adaptive urban morphogenesis: Modeling China’s hyper-growth cities under uncertainty
Year: 2025
Type: article
Abstract: China’s hyper-growth cities face unprecedented uncertainty arising from intertwined economic, social, and environmental stresses that challenge traditional static approaches to urban planning. This article introduces the novel concept of adaptive urban morphogenesis—an evolving and dynamic configuration of urban structure and function—enabled by the synergistic integration of quantum computing (QC) and artificial intelligence (AI). We propose employing QC to manage inherent uncertainties and to deliver computationally feasible multi-objective combinatorial optimization solutions, such as dynamic resource allocation and resilient infrastructure design. In parallel, AI processes extensive urban datasets, extracts complex patterns, and generates real-time predictive insights. Together, these technologies establish a closed-loop feedback system: AI feeds QC simulations with predictions, while QC delivers the best adaptive solutions under uncertainty that subsequently inform AI models. This framework is designed to capture the rapid evolution of China’s urban economies and offers a paradigm shift toward forward-thinking, simulation-driven urban planning.
Author: Ehsan Dorostkar
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414403824