Machine learning enhances light-beam performance at the advanced light source

A team of researchers at Berkeley Lab and UC Berkeley has successfully demonstrated how machine-learning tools can improve the stability of light beams' size for science experiments at a synchrotron light source via adjustments that largely cancel out unwanted fluctuations.

Synopsis: Noisy Synchrotron? Machine Learning Has the Answer

Machine-learning algorithms could allow researchers to substantially reduce unwanted fluctuations in the widths of the electron beams produced at synchrotrons.[Physics] Published Wed Nov 06, ...

Wed 6 Nov 19 from APS Physics

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