Mathematical Modeling of Broadband Quantum Noise Suppression in Hybrid Quantum Networks for Acoustic Frequency Sensing

This study investigates the optimization of hybrid quantum networks, integrating two-color Einstein-Podolsky Rosen (EPR) light sources and tunable spin oscillators, to enhance Gravitational-Wave Detection (GWD) and distributed quantum sensing. Initial challenges with high quadrature amplitudes were addressed by adjusting frequency and coupling scales, significantly reducing noise below the standard quantum limit. Time evolution analyses demonstrated damped oscillations stabilizing over time, while Power Spectral Density (PSD) plots confirmed effective broadband noise suppression. Design enhancements, such as cryogenic cooling and low loss cavities, further lowered thermal noise and decay rates, improving system scalability. However, residual amplitude clipping and PSD peaks indicate potential nonlinearities and decoherence, suggesting areas for refinement. The study advocates for experimental validation using unclipped models and cost-effective cooling strategies, highlighting the framework’s potential for quantum-enhanced metrology in astrophysics and geophysics. Future research should address scalability and cost challenges to enable practical deployment.