Pondering speedy neutrinos
Regarding “Hints of a flaw in special relativity” (SN: 10/22/11, p. 18), there could be a simple explanation for neutrinos being measured as traveling faster than the speed of light in a vacuum. While a vacuum is typically defined as a space entirely devoid of matter, in fact a vacuum is a busy medium with virtual particles continually being created and destroyed. Light passing through a vacuum is affected by such activity.
Neutrinos have such low interactions that they can pass through a lead wall several hundred light-years thick without slowing down. The ultimate speed in the universe is, therefore, that of neutrinos, not photons in a vacuum. It isn’t so much that neutrinos are faster than light in a vacuum, rather that light is slower than neutrinos whether or not the neutrinos are in a vacuum.
As for special relativity, it relies on the constancy of the speed of light, not on any particular speed of light. Substituting the speed of neutrinos would not affect the measurable results.
Robert Berliner, Los Angeles, Calif.
Such interactions in a vacuum do slow light down, a phenomenon called the Scharnhorst effect. But this effect is much too insignificant to explain how neutrinos could arrive at a detector 60 nanoseconds earlier than light in a race covering only 730 kilometers. That 60 nanoseconds corresponds to a margin of victory in that race of about 18 meters. A photon slowed by the Scharnhorst effect would lag behind a photon without such a slowdown by only about the width of an atom—after racing for the current age of the universe. —Tom Siegfried
While it seems unlikely the faster-than-light neutrinos are really that fast, it is important to find the cause of the experimental error (if there was an error). Scientific revolutions are the result of years of ignoring data that “don’t fit” until finally the burden of outlier data accumulates enough that someone questions existing paradigms. So while the editorial “With scientific puzzles, all the pieces have to fit” (SN: 1/28/12, p. 2) was mostly excellent, I object strongly to the final phrase, “if it doesn’t fit, you must omit.” Rather, “if it doesn’t fit, you must understand why.” Even if the outlier data were in error, understanding the cause will improve future experiments. And you never know, maybe it really shouldn’t have fit!
Al Bogart, Framingham, Mass.