High-Precision Ground Characterization of Test-Mass Magnetic Properties for the Taiji Gravitational Wave Mission via a Physics-Informed Neural Framework
This paper proposes an AI-enhanced Differentiable Weighted Least Squares (AI-WLS) framework that combines a dilated residual network with a physical solver to achieve high-precision characterization of test-mass magnetic properties by effectively suppressing non-stationary noise in torsion-pendulum measurements for the Taiji gravitational wave mission.