AxionQM: A Supervisory Quantum Management Framework for Long-Horizon Survivability Under Sustained Noise

Abstract Quantum systems are commonly evaluated using short-horizon performance metrics such as logical error rates, thresholds, and instantaneous fidelity. While necessary, these metrics provide limited insight into system behavior under sustained operation, where noise, drift, and irreversible failure mechanisms accumulate over time. This work introduces AxionQM, a supervisory quantum management framework designed to evaluate long-horizon survivability rather than short-horizon correctness. AxionQM models quantum system operation as a regime-aware management problem with explicit treatment of degradation, stochastic noise, and absorbing failure states. Using extended endurance simulations with correlated noise, drift, and leakage-like processes, we demonstrate probabilistic survivability behavior in which identical configurations may either persist or fail catastrophically depending on stochastic evolution and supervisory policy. The results show that supervisory control strategy materially influences long-term outcomes and that conventional threshold-based evaluation is insufficient to characterize sustained operation. AxionQM provides a system-level, simulation-based methodology for endurance-oriented analysis of quantum systems without introducing new algorithms, hardware claims, or error-correction mechanisms.