Improving cosmological reach of a gravitational wave observatory using Deep Loop Shaping
Jonas Buchli, Brendan Tracey, Tomislav Andric, Christopher Wipf, Yu Him Justin Chiu, Matthias Lochbrunner, Craig Donner, Rana X. Adhikari, Jan Harms, Iain Barr, Roland Hafner, Andrea Huber, Abbas Abdolmaleki, Charlie Beattie, Joseph Betzwieser, Serkan Cabi, Jonas Degrave, Yuzhu Dong, Leslie Fritz, Anchal Gupta, Oliver Groth, Sandy Huang, Tamara Norman, Hannah Openshaw, et al.
改进引力波观测站的低频灵敏度将解锁对中质量黑洞合并,二元黑洞偏心率的研究,并为双中子星合并的多信使观测提供早期预警。 今天的镜面稳定控制注入了有害噪音,构成了灵敏度改善的主要障碍。 我们通过Deep Loop Shaping消除了这种噪声,这是一种使用频域奖励的强化学习方法。 我们在LIGO利文斯顿天文台(LLO)上证明了我们的方法论。 我们的控制器将10-30Hz频段的控制噪声降低了30倍以上,子频段的控制噪声高达100倍,超过了量子极限所驱动的设计目标。 这些结果突出了Deep Loop Shaping在改善当前和未来GW观测站以及更广泛的仪器和控制系统方面的潜力。
Improved low-frequency sensitivity of gravitational wave observatories would unlock study of intermediate-mass black hole mergers, binary black hole eccentricity, and provide early warnings for multi-messenger observations of binary neutron star mergers. Today's mirror stabilization control injects harmful noise, constituting a major obstacle to sensitivity improvements. We eliminated this noise through Deep Loop Shaping, a reinforcement learning method using frequency domain rewards. We proved ...