Kavli Affiliate: Rana X. Adhikari
| First 5 Authors: , , , ,
| Summary:
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 our methodology on the LIGO
Livingston Observatory (LLO). Our controller reduced control noise in the
10–30Hz band by over 30x, and up to 100x in sub-bands surpassing the design
goal motivated by the quantum limit. These results highlight the potential of
Deep Loop Shaping to improve current and future GW observatories, and more
broadly instrumentation and control systems.
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