A physics-informed neural framework called AI-WLS reduces estimation errors for test-mass remanent magnetic moment and susceptibility to levels required by Taiji by dynamically suppressing non-stationary noise in torsion-pendulum data.
Karnesiset al., (2022), arXiv:2209.04358 [gr-qc]
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Black hole populations with finite-width mass distributions exhibit universal late-time evaporation-driven evolution that produces characteristic power-law suppression of induced gravitational waves, directly linking the asymptotic GW spectrum to the evaporation law.
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High-Precision Ground Characterization of Test-Mass Magnetic Properties for the Taiji Gravitational Wave Mission via a Physics-Informed Neural Framework
A physics-informed neural framework called AI-WLS reduces estimation errors for test-mass remanent magnetic moment and susceptibility to levels required by Taiji by dynamically suppressing non-stationary noise in torsion-pendulum data.
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Universal Suppression of Gravitational Waves from Black Hole Evaporation Dynamics
Black hole populations with finite-width mass distributions exhibit universal late-time evaporation-driven evolution that produces characteristic power-law suppression of induced gravitational waves, directly linking the asymptotic GW spectrum to the evaporation law.