The uncertainty of science: New data now suggests that the subatomic particle called the muon is slightly more magnetic that predicted by the standard model of particle physics, a result that if confirmed will require a major rethinking of that standard model.
In 2001, researchers with the Muon g-2 experiment, then at Brookhaven, reported that the muon was a touch more magnetic than the standard model predicts. The discrepancy was only about 2.5 times the combined theoretical and experimental uncertainties. That’s nowhere near physicists’ standard for claiming a discovery: 5 times the total uncertainty. But it was a tantalizing hint of new particles just beyond their grasp.
So in 2013, researchers hauled the experiment to Fermi National Accelerator Laboratory (Fermilab) in Illinois, where they could get purer beams of muons. By the time the revamped experiment started to take data in 2018, the standard model predictions of the muon’s magnetism had improved and the difference between the experimental results and theory had risen to 3.7 times the total uncertainty.
Now, the g-2 team has released the first result from the revamped experiment, using 1 year’s worth of data. And the new result agrees almost exactly with the old one, the team announced today at a symposium at Fermilab. The concordance shows the old result was neither a statistical fluke nor the product of some undetected flaw in the experiment, says Chris Polly, a Fermilab physicist and co-spokesperson for the g-2 team. “Because I was a graduate student on the Brookhaven experiment, it was certainly an overwhelming sense of relief for me,” he says.
Together, the new and old results widen the disagreement with the standard model prediction to 4.2 times the experimental and theoretical errors.
That result is still not five times what theory predicts — the faux standard physicists apparently use to separate a simple margin of error and a true discovery — but it is almost that high, has been found consistently in repeated tests, and appears to be an unexplained discrepancy.
Not that I take any of this too seriously. If you read the entire article, you will understand. There are so many areas of uncertainty, both in the data and in the theories that this research is founded on, that the wise course is to treat it all with a great deal of skepticism. For example, the anomaly reported involves only 2.5 parts in 1 billion. While this data is definitely telling us something, but it is so close to the edge of infinitesimal that one shouldn’t trust it deeply.
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