Detecting Dark Energy-Quantum Spin Resonance via Hybrid Quantum-Classical Systems with Adaptive ML Tuning

In this paper, I propose a novel experimental framework to explore the possible interaction between dark energy and quantum spin using advanced resonance spectroscopy techniques. By integrating a hybrid quantum-classical system, adaptive quantum error correction, and machine learning algorithms for optimized resonance tuning, this approach aims to detect and analyze the spectroscopic signature of dark energy's influence at the quantum level. This interdisciplinary proposal offers a new pathway toward understanding one of the most mysterious components of our universe and opens the door for future experimental verification.