Quantum Bayesian Networks for Reliability Analysis of Unmanned Systems

Siddhesh Salfale, Gunjana Dhakad, Sonia Bara, Abhinav Krishnan T. K., Indranil Hazra

Published Sep 10, 2025• 1 citation

Abstract

Abstract Unmanned systems play a crucial role in modern cyber-physical systems, supporting applications in defense, surveillance, and commercial operations. As these systems grow in scale and complexity, their reliability becomes increasingly challenging to assess due to intricate dependencies among components and subsystems. Traditional system reliability analysis using classical Bayesian networks struggle with computational scalability, limiting their applicability in large-scale systems. This study explores quantum Bayesian networks (QBNs) as a novel approach for reliability analysis and prediction in unmanned systems. A quantum circuit-based Bayesian network model is developed to represent component dependencies, leveraging quantum computing advantages such as superposition and entanglement. The methodology is applied to the communication system of an unmanned surface vessel using IBM’s Qiskit and executed on a supercomputer using quantum simulators. Results demonstrate the potential of quantum computing to enhance reliability and risk assessments, offering a scalable solution for applications relating to complex systems.

DOI: 10.1115/imece-india2025-160308

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