No, of course not.
Apart from the usual reasons, he’s off by more than a factor of six.
If you play with the numbers, it looks like Simon Singh (the popular science writer who reported the “discovery” Homer made as a throwaway joke in a 1998 Simpsons episode) made the classic physics mistake of losing track of a factor of . In particular, it looks like he mistakenly thought that the Planck constant, , was equal to the reduced Planck constant, , divided by , when actually it’s times . So while Singh read Homer’s prediction as 123 GeV, surprisingly close to the actual Higgs mass of 125 GeV found in 2012, in fact Homer predicted the somewhat more embarrassing value of 775 GeV.
That was boring. Let’s ask a more interesting question.
I’ve talked before about how it seems impossible that string theory will ever make any testable predictions. The issue boils down to one of too many possibilities: string theory predicts different consequences for different ways that its six (or seven for M theory) extra dimensions can be curled up. Since there is an absurdly vast number of ways this can be done, anything you might want to predict (say, the mass of the electron) has an absurd number of possible values.
Gordon Kane and collaborators get around this problem by tackling a different one. Instead of trying to use string theory to predict things we already know, like the mass of the electron, they assume these things are already true. That is, they assume we live in a world with electrons that have the mass they really have, and quarks that have the mass they really have, and so on. They assume that we live in a world that obeys all of the discoveries we’ve already made, and a few we hope to make. And, they assume that this world is a consequence of string (or rather M) theory.
From that combination of assumptions, they then figure out the consequences for things that aren’t yet known. And in a 2011 paper, they predicted the Higgs mass would be between 105 and 129 GeV.
I have a lot of sympathy for this approach, because it’s essentially the same thing that non-string-theorists do. When a particle physicist wants to predict what will come out of the LHC, they don’t try to get it from first principles: they assume the world works as we have discovered, make a few mild extra assumptions, and see what new consequences come out that we haven’t observed yet. If those particle physicists can be said to make predictions from supersymmetry, or (shudder) technicolor, then Gordon Kane is certainly making predictions from string theory.
So why haven’t you heard of him? Even if you have, why, if this guy successfully predicted the mass of the Higgs boson, are people still saying that you can’t make predictions with string theory?
Trouble is, making predictions is tricky.
Part of the problem is timing. Gordon Kane’s paper went online in December of 2011. The Higgs mass was announced in July 2012, so you might think Kane got a six month head-start. But when something is announced isn’t the same as when it’s discovered. For a big experiment like the Large Hadron Collider, there’s a long road between the first time something gets noticed and the point where everyone is certain enough that they’re ready to announce it to the world. Rumors fly, and it’s not clear that Kane and his co-authors wouldn’t have heard them.
Assumptions are the other issue. Remember when I said, a couple paragraphs up, that Kane’s group assumed “that we live in a world that obeys all of the discoveries we’ve already made, and a few we hope to make“? That last part is what makes things tricky. There were a few extra assumptions Kane made, beyond those needed to reproduce the world we know. For many people, some of these extra assumptions are suspicious. They worry that the assumptions might have been chosen, not just because they made sense, but because they happened to give the right (rumored) mass of the Higgs.
If you want to predict something in physics, it’s not just a matter of getting in ahead of the announcement with the right number. For a clear prediction, you need to be early enough that the experiments haven’t yet even seen hints of what you’re looking for. Even then, you need your theory to be suitably generic, so that it’s clear that your prediction is really the result of the math and not of your choices. You can trade off aspects of this: more accuracy for a less generic theory, better timing for looser predictions. Get the formula right, and the world will laud you for your prediction. Wrong, and you’re Homer Simpson. Somewhere in between, though, and you end up in that tricky, tricky grey area.
Like Gordon Kane.