Case Study: Max Planck Institute for Gravitational Physics detects gravitational waves with MathWorks deep learning and reinforcement learning

Max Planck Institute for Gravitational Physics - Customer Case Study

The Max Planck Institute for Gravitational Physics faced the complex challenge of detecting extremely faint gravitational wave signals buried within noisy interferometer data and controlling the highly sensitive, multi-mirror optical systems used to detect them. Their goal was to improve detection accuracy and simplify the intricate control processes that previously required extensive expert engineering.

Using MathWorks tools, including Deep Learning Toolbox and Reinforcement Learning Toolbox, the institute implemented a two-part AI solution. They developed a convolutional neural network that successfully identified gravitational wave signals, recovering all known events and even discovering a previously missed black hole merger. Furthermore, they created a reinforcement learning agent trained in a Simulink simulation environment to autonomously control and align the interferometer's optics. This MathWorks-powered solution enhanced detection capabilities and demonstrated the first-ever successful implementation of AI for alignment control at a gravitational wave detector, leading to improved sensitivity and operational reliability.

Max Planck Institute for Gravitational Physics

Nikhil Mukund

Scientist