Back in 2014, CERN released the data from its Large Hadron Collider (LHC) experiments onto an online portal called the Open Data portal. It was an unprecedented move, making data from the LHC’s experiments available to those who don’t have access to a particle accelerator. It’s not completely up-to-date; there’s a three-year embargo on results, so, generally speaking, the most recent data being uploaded is from the year 2014. This was the first time results of any particle collider experiment have been released to the public, and now it’s produced results.
Last week, a team from MIT released an article in Physical Review Letters that used data from the Compact Muon Solenoid (CMS), one of the LHC’s main detectors, to explain a feature within high-energy particle collisions. When protons collide at very high speeds, they release jets of quarks and gluons. The MIT team was able to show, using CMS data, that the same equation can predict both the pattern of these jets and the energy of the particles produced from a proton collision. Scientists suspected this was indeed the case, and now that hypothesis has been verified.
This is revolutionary because there’s been a reluctance in particle physics to make information available publicly. Jesse Thaler, one of the scientists on the project, told Phys.org, “The worry was, if you made the data public, then you would have people claiming evidence for new physics when actually it was just a glitch in how the detector was operating.” He continues to say that there was a certain arrogance that may have played into it as well: the belief that, if in-house scientists couldn’t make a discovery based on this data, then there was no way others could.
That’s why this discovery is so encouraging. The equation in and of itself isn’t revolutionary; it confirms something most scientists already agreed with. But the fact that the LHC’s public data led to a discovery outside the organization is a big step. Perhaps it will encourage other particle colliders to make their data available as well. Thaler said, “Our work here shows that we can understand in general how to use this open data, that it has scientific value, and that this can be a stepping stone to future analysis of more exotic possibilities.”