It’s been published several places, but you’ve probably seen this headline:
No, these physicists haven’t actually shown that the Universe isn’t expanding at an accelerated rate.
What they did show is that the original type of data used to discover that the universe was accelerating back in the 90’s, measurements of supernovae, doesn’t live up to the rigorous standards that we physicists use to evaluate discoveries. We typically only call something a discovery if the evidence is good enough that, in a world where the discovery wasn’t actually true, we’d only have a one in 3.5 million chance of getting the same evidence (“five sigma” evidence). In their paper, Nielsen, Guffanti, and Sarkar argue that looking at a bigger collection of supernovae leads to a hazier picture: the chance that we could get the same evidence in a universe that isn’t accelerating is closer to one in a thousand, giving “three sigma” evidence.
This might sound like statistical quibbling: one in a thousand is still pretty unlikely, after all. But a one in a thousand chance still happens once in a thousand times, and there’s a long history of three sigma evidence turning out to just be random noise. If the discovery of the accelerating universe was new, this would be an important objection, a reason to hold back and wait for more data before announcing a discovery.
The trouble is, the discovery isn’t new. In the twenty years since it was discovered that the universe was accelerating, people have built that discovery into the standard model of cosmology. They’ve used that model to make other predictions, explaining a wide range of other observations. People have built on the discovery, and their success in doing so is its own kind of evidence.
So the objection, that one source of evidence isn’t as strong as people thought, doesn’t kill cosmic acceleration. What it is is a “maybe”, showing that there is at least room in some of the data for a non-accelerating universe.
People publish “maybes” all the time, nothing bad about that. There’s a real debate to be had about how strong the evidence is, and how much it really establishes. (And there are already voices on the other side of that debate.)
But a “maybe” isn’t news. It just isn’t.
Science journalists (and university press offices) have a habit of trying to turn “maybes” into stories. I’ve lost track of the times I’ve seen ideas that were proposed a long time ago (technicolor, MOND, SUSY) get new headlines not for new evidence or new ideas, but just because they haven’t been ruled out yet. “SUSY hasn’t been ruled out yet” is an opinion piece, perhaps a worthwhile one, but it’s no news article.
The thing is, I can understand why journalists do this. So much of science is building on these kinds of “maybes”, working towards the tipping point where a “maybe” becomes a “yes” (or a “no”). And journalists (and university press offices, and to some extent the scientists themselves) can’t just take time off and wait for something legitimately newsworthy. They’ve got pages to fill and careers to advance, they need to say something.
I post once a week. As a consequence, a meaningful fraction of my posts are garbage. I’m sure that if I posted every day, most of my posts would be garbage.
Many science news sites post multiple times a day. They’ve got multiple writers, sure, and wider coverage…but they still don’t have the luxury of skipping a “maybe” when someone hands it to them.
I don’t know if there’s a way out of this. Maybe we need a new model for science journalism, something that doesn’t try to ape the pace of the rest of the news cycle. For the moment, though, it’s publish or perish, and that means lots and lots of “maybes”.
EDIT: More arguments against the paper in question, pointing out that they made some fairly dodgy assumptions.
EDIT: The paper’s authors respond here.