From Nature Italy May 20, 2022: CDF co-spokesperson Giorgio Chiarelli tells the story of how Italy contributed to the measurement of the W boson mass, opening a door on new physics. For more than 10 years after the Tevatron detector at Fermilab produced the last crashes between protons and antiprotons, the collaboration announced the most precise measure of the W boson mass ever achieved.

From the Nature Briefing, May 13, 2022: Based on data recorded with the CDF II detector at Fermilab between 2002 and 2011 at the Tevatron, the collaboration reconstructed more than 4 million W boson candidates through their decays into an electron or muon accompanied by the respective neutrino. The CDF Collaboration stated their result “suggests the possibility of improvements to the standard model calculation or of extensions to it”.

From WIRED, April 18, 2022: A collaboration of over four hundred scientists, hundreds of measurements and a 0.1 percent too heavy W boson have led to a tiny discrepancy in the Standard Model theory that could be a huge shift in fundamental physics.

From Gizmodo, April 7, 2022: A collaboration of 400 researchers have precisely measured the mass of the W boson and to their surprise found that the boson is more massive than predicted by the Standard Model of particle physics. All the data was collected from experiments at the four-story-tall, 4,500-ton Collider Detector (CDF-II for short) at Fermilab’s Tevatron accelerator.

From the BBC, April 7, 2022: Scientists of the CDF collaboration have found a tiny difference in the mass of the W Boson compared with what the theory says it should be – just 0.1%. If confirmed by other experiments, the implications could be enormous and could challenge the Standard Model of particle physics.

Illustration of four scientists in white lab coats, two of whom are typing, two of whom are looking at and drawing on a screen with equations and 3D images.

Over time, particle physics and astrophysics and computing have built upon one another’s successes. That coevolution continues today. New physics experiments require computing innovation, including cluster computing for the Tevatron, and more recently machine learning and quantum problem-solving.