AI RESEARCH
The Average Relative Entropy and Transpilation Depth determines the noise robustness in Variational Quantum Classifiers
arXiv CS.LG
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ArXi:2603.21300v1 Announce Type: cross Variational Quantum Algorithms (VQAs) have been extensively researched for applications in Quantum Machine Learning (QML), Optimization, and Molecular simulations. Although designed for Noisy Intermediate-Scale Quantum (NISQ) devices, VQAs are predominantly evaluated classically due to uncertain results on noisy devices and limited resource availability. Raising concern over the reproducibility of simulated VQAs on noisy hardware.