Realization of measurement-based quantum computing model in fault-tolerant distributed quantum systems

The constraints on achieving scalable and fault-tolerant quantum computation, together with the intrinsic architectural limitations of monolithic quantum processors, have motivated the exploration of Distributed Quantum Computing systems, where multiple quantum nodes collaborate through entanglement-assisted links to execute large-scale algorithms as a single logical computational platform. As different computational paradigms offer distinct trade-offs, identifying the most suitable architecture for scalable, efficient, and fault-tolerant quantum computing becomes crucial. This paper focuses on the two most widely adopted models, Circuit-Based and Measurement-Based Quantum Computing, and provides a novel and comprehensive comparison across five critical dimensions: algorithm design, hardware heterogeneity, inter-node communication, fault tolerance, and resource efficiency, establishing that MBQC offers distinct architectural and operational advantages for DQC. Building on this comparative framework, the work presents a mathematical perspective through a focused case study on MBQC, illustrating how adaptive measurements and classical feedforward can contribute to measurement-driven robustness against logical errors under realistic noise conditions. The paper concludes by outlining key challenges and future directions for the advancement of robust distributed quantum architectures.