Authors:
V. Sabaresan, Mohaideen Fathima P, C. Gayathri, R. Vanitha, Samson Davidson, S. Sharan Jeev, S. J. Vimal Aravintha, S. Tejas

Addresses:
Department of Computer Science and Engineering, St Joseph's Institute of Technology, Chennai, Tamil Nadu, India. Department of Computer Science and Engineering in Artificial Intelligence and Machine Learning, Easwari Engineering College, Ramapuram, Chennai, Tamil Nadu, India. Department of Computer Science and Engineering, Easwari Engineering College, Ramapuram, Chennai, Tamil Nadu, India. Department of Computer Science and Engineering, KCG College of Technology, Chennai, Tamil Nadu, India. School of Computer Science and Information Technology, University of Edinberg, Lusaka, Zambia. Department of Cybersecurity, University of Texas at Dallas, Richardson, Texas, United States of America. Department of Data Science, Indiana University Bloomington, Bloomington, Indiana, United States of America. Department of Data Science, Analytics and Engineering, Arizona State University, Tempe, Arizona,  United States of America. 

Abstract:

The execution of fault-tolerant quantum computing must be reliable with varying hardware quality, workload intensities and available processing resources during execution. This paper proposes a resource-adaptive framework that integrates intelligent error mitigation, coherent information handling, feedback-driven scheduling, and recovery control into a single processing path. To cover diverse cases of workload pressure, device readiness, coherence retention, mitigation response, recovery behavior, and output reliability, researchers conducted a study that yielded 265 experimental instances for the dataset. For evaluation, researchers implemented controlled data processing and graph support in Python; spreadsheet data processing in a spreadsheet; and document data processing using a document-based inspection method. The proposed method continuously correlates workload and device conditions, makes processing decisions based on the correlation, applies mitigations when it detects disturbances, and retains useful information before producing reliable output. The study focuses on adaptation rather than protection policies; resources can shift to portions of an execution that require greater protection. Experimental observations show that coordinated control increases stability, extends coherent operation and reduces avoidance recovery activity. The resulting design is a small example of how to build resilient quantum workflows that can adapt to varying hardware conditions without requiring protection settings or undue resource reservations.

Keywords: Fault-Tolerant Quantum Computing; Resource Adaptation; Error Mitigation; Coherent Information Processing; Feedback Control; Quantum Computers; Fault-Management Principles.

Received on: 01/11/2025, Revised on: 26/12/2025, Accepted on: 13/02/2026, Published on: 03/06/2026

DOI: 10.69888/FTSCIS.2026.000767

FMDB Transactions on Sustainable Critical Infrastructures, 2026 Vol. 1 No. 2, Pages: 126-135

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