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Home»Tools»Use AI to perceive the universe more deeply
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Use AI to perceive the universe more deeply

versatileaiBy versatileaiSeptember 5, 2025No Comments7 Mins Read
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Science

Author published on September 4th, 2025

Brendan Tracy and Jonas Book

Our new deep loop shaping method improves control of gravitational wave observatory and helps astronomers better understand the dynamics and formation of the universe.

To help astronomers study the most powerful processes in the universe, our team has used AI to stabilize one of the most sensitive observation instruments ever built.

A paper published today in Science introduces Deep Loop Shaping, a new AI method that unlocks next-generation gravitational wave science. Deep loop shaping reduces noise in the station’s feedback system, improves control, and stabilizes the components used to measure gravitational waves. This is a small ripple in the fabric of space and time.

These waves are generated by events such as neutron star collisions and black holes mergers. Our methods help astronomers gather important data to understand the dynamics and formation of the universe, and better test the fundamental theories of physics and cosmology.

Caltech and GSSI (Gran Sasso Science Institute) have worked with Ligo (the Gravitational Wave Observatory for Laser Interferometers) to develop deep loop shaping to prove the method at the Livingston, Louisiana observatory.

Ligo measures the properties and origins of gravitational waves with incredible accuracy. However, slight vibrations can disrupt measurements, even from waves crashing 100 miles away on the Gulf Coast. To function, Ligo relies on thousands of control systems to keep every part in near perfect alignment and adapt to environmental disorders with continuous feedback.

Deep loop shaping reduces noise levels 30-100 times in the most unstable and difficult feedback loops in Ligo, improving the stability of highly sensitive interferometer mirrors. By applying the method to all of Ligo’s mirror control loops, astronomers can help detect and collect around hundreds of events a year.

In the future, deep loop types could also be applied to many other engineering problems, including vibration suppression, noise cancellation, and highly dynamic or unstable systems, which are important in aerospace, robotics and structural engineering.

Measurement of the universe

Ligo uses laser light interference to measure the properties of gravitational waves. By studying these properties, scientists can understand what caused them and where they came from. The observatory’s laser reflects a mirror located four kilometers away, housed in the world’s largest vacuum chamber.

An aerial view of Rigo (a laser interferometer gravitational wave observatory) in Livingston, Louisiana, USA. The laser at the observatory reflects mirrors located four kilometers away. Photo credits for Caltech/MIT/Ligo Lab.

Since first detecting gravitational waves produced by a pair of colliding black holes in 2015 and examining Albert Einstein’s predictions of relativity, Rigo’s measurements have changed our understanding of the universe deeply.

With this observatory, astronomers detected hundreds of black holes and neutron star collisions, and found new black holes formed by neutron star collisions, studying the creation of heavy elements such as gold.

Astronomers already know a lot about the largest and smallest black holes, but data on intermediate mass black holes is limited. This is considered a “missing link” to understand galaxy evolution.

Until now, Ligo has not been able to observe most of these systems. To help astronomers capture more details and data about this phenomenon, they worked to improve the most challenging parts of the control system and expand the extent to which they are far apart from these events.

“

Using gravity instead of light to study the universe is like listening rather than seeing it. This allows us to tune to the bass.

Lana Adicali, Professor of Physics in California, 2025

Reducing noise and stabilizing the system

As gravitational waves pass through Ligo’s two 4-kilometer arms it distorts the space between them, changing the distance between the mirrors at both ends. These small differences in length are measured using optical interference for accuracy of 10^-19 meters. This is 1/10’000 of the size of a proton. Measurements require this small Ligo detector mirror to be kept very quiet, isolated from environmental disturbances.

Close-up photos of Ligo, which use strong lasers and mirrors to detect gravitational waves in space, are generated by events such as collisions and black holes mergers. Photo credits for Caltech/MIT/Ligo Lab.

This requires one system for passive mechanical separation and another control system to actively suppress vibrations. Less control will swing the mirror and make it impossible to measure anything. But too much control actually amplifies the vibrations of the system and instead of suppressing them, it makes the signal own over a certain frequency range.

Known as “control noise,” these vibrations are important blockers for improving Ligo’s ability to peer into space. Our team has designed deep loop shaping to remove the controller as a meaningful source of noise, beyond traditional methods, such as linear control design methods currently in operation.

More effective control systems

Deep loop shaping utilizes reinforcement learning methods using frequency domain rewards to outperform cutting-edge feedback control performance.

In the simulated Ligo environment, we trained a controller to avoid amplification of noise in the observation bands used to measure gravitational waves.

FIG. 10 illustrates the complex system of Ligo’s complex laser and mirrors. The distributed control system actively regulates the mirror to counter laser radiation pressure and vibrations from external sources.

Through repeated interactions guided by frequency domain rewards, the controller learns to suppress control noise in the observation band. In other words, our controllers learn to stabilize the mirror without adding any harmful control noise, lowering the noise level by more than ten times the amount of vibration caused by quantum fluctuations in the radiation pressure of the light reflecting the mirror.

Powerful performance across simulation and hardware

We tested the controller on a Real Rigo system in Livingston, Louisiana, USA. I found it works well in hardware just like the simulation.

Our results show that deep loop shaping controls up to 30-100 times more noise than existing controllers, eliminating the most unstable and difficult feedback loop as a meaningful source of noise for LIGO.

A line chart showing the resulting control noise spectrum using a deep loop shaping method. The most unstable and difficult feedback control loop has 30-100 improvements in the injected control noise level.

Repeated experiments confirmed that the controller stabilizes the station’s system for a long period of time.

A better understanding of the nature of the universe

Deep loop shaping pushes the boundaries of what is currently possible in astrophysics by solving blockers important for studying gravitational waves.

Applying deep loop shaping across Ligo’s mirror control system opens up ways to widen the cosmological reach, with the potential to eliminate noise from the control system itself.

Not only will existing gravitational wave observatories be further measured and significantly improve how the source of dimming is measured, but our work is also hopeful that it will affect future observatory designs on both Earth and space, and will ultimately help connect missed links across the universe for the first time.

Find out more about our work

Acknowledgments

This study was conducted by Jonas Buffrey, Brendan Tracy, Tomislav Andrick, Christopher Whip, Yuu His Justin Chiu, Matthias Lockbrunner, Craig Donner, Lana X. Adhikari, Jean Harms, Ian Barr, Roland Hafner, Andrea Huber, Abbas Abdolmaleki, Chardolmaleki, Yoberkabi, Jonas DeGraive, Yuzu Don, Leslie Fritz, Ankal Gupta, Oliver Gross, Sandy Hun, Tamara Norman, Hannah Open Show, Jameson Rollins, Greg Thornton, George van den Dristier, Marx Warfmeyer, Pushmeet Kuffmayer, Martin Riett, GSSI and GDM.

We thank the fantastic Ligo Instrument Team for their tireless work of maintaining, running and supporting experiments.

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