Enhanced model for prediction of residual gas effects in space gravitational wave detection missions

物理 放气 噪音(视频) 残余物 布朗运动 辐射计 计算物理学 统计物理学 绝热过程 热的 引力波 万有引力 探路者 热平衡 热涨落 工作(物理) 机械
作者
K Liu,L Liu,X D Hu,Z B Zhou
出处
期刊:Classical and Quantum Gravity [IOP Publishing]
卷期号:43 (1): 015021-015021
标识
DOI:10.1088/1361-6382/ae2b1e
摘要

Abstract Space gravitational wave detection missions impose extremely stringent requirements for non-gravitational disturbances on the inertial reference, where gas-related noise may be the most critical source. The gas-related noise mainly includes Brownian noise, radiometer effect, and outgassing effect. In general, Brownian noise and radiometer effects can be evaluated by introducing a thermal accommodation coefficient (TAC). However, TAC cannot accurately represent the proportion of inelastic collisions σ . In order to address this limitation, we introduced a theoretical value of σ based on three assumptions that the single-component gas molecules will be adsorbed on the empty sites of the solid surface with a fixed probability under equilibrium conditions, that the single-component gas molecules will also be adsorbed by the occupied sites with another fixed probability under equilibrium conditions, and that the average desorption activation energy of the adsorbed gas molecules remained on the solid surface increases progressively over time during the outgassing process. With the σ , we proposed an enhanced gas-related noise model which exhibits an excellent fit to the in-orbit experimental data of LISA Pathfinder and the torsion experimental results in our group. This model theoretically derives an improved expression for outgassing rate, revealing that the pressure decay scaling as t −0.8 and the activation temperature of residual gases is (8450 ± 224) K. This model demonstrates predictive capability in forecasting gas-related noise for the LISA mission. Furthermore, this work also provides a universal tool for optimizing future gravitational wave observatory designs and accelerating their operational readiness.

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