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Scientists Develop Machine Learning Techniques to Shed New Light on Pulsars


the Vela radio pulsar

Researchers studied pulses of Vela from observations of over three hours, with around 120,000 pulses per observation.

Credit: Wikipedia

Machine learning techniques developed by scientists at Rochester Institute of Technology are revealing important information about how pulsars — rapidly rotating neutron stars — behave. In a study published in Monthly Notices of the Royal Astronomical Society, the researchers outlined their new techniques and how they applied to study Vela, the brightest radio pulsar in the sky.

"To do this in human terms takes a lot of time and results in a lot of mistakes," says Carlos Lousto, lead author of the study and a professor in the School of Mathematical Sciences. "The technology we have developed opens up a plethora of applications in astrophysics."

The researchers collected observations over four days in January and March 2021 and studied their statistical properties with machine learning techniques.

From Rochester Institute of Technology
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