To identify signs of particles like the Higgs boson, CERN researchers work with mountains of data generated by LHC collisions.

Hunting for evidence of an object whose behavior is predicted by existing theories is one thing. But having successfully observed the elusive boson, identifying new and unexpected particles and interactions is an entirely different matter.

To speed up their analysis, physicists feed data from the billions of collisions that occur in LHC experiments into machine learning algorithms. These models are then trained to identify anomalous patterns.