A Bump at the Large Hadron Collider

Very busy, so just a quickie today. Yesterday the good folk at the Large Hadron Collider announced their latest batch of results. You can find the complete set from the CMS experiment here and from ATLAS here.

The result that everyone is talking about is shown in the following graph, which shows the number of diphoton events as a function of energy:

Atlas_Bump

Attention is focussing on the apparent “bump” at around 750 GeV; you can find an expert summary by a proper particle physicist here and another one here.

It is claimed that the “significance level” of this “detection” is 3.6σ. I won’t comment on that precise statement partly because it depends on the background signal being well understood but mainly because I don’t think this is the right language in which to express such a result in the first place. Experimental particle physicists do seem to be averse to doing proper Bayesian analyses of their data.

However if you take the claim in the way such things are usually presented it is roughly equivalent to a statement that the odds against this being a real detection are greater that 6000:1. If any particle physicists out there are willing to wager £6000 for £1 of mine that this result will be confirmed by future measurements then I’d happily take them up on that bet!

P.S. Entirely predictably there are 10 theory papers on today’s ArXiv offering explanations of the alleged bump, none of which says that it’s a noise feature..

 

 

3 Responses to “A Bump at the Large Hadron Collider”

  1. I’m convinced that there’re theorists who have LaTeX scripts set up that they can plug arbitrary numbers from LHC papers and instantly produce papers for ArXiv…

  2. Too disappointed. Someone mentioned your bet and I thought that you were offering the exact opposite odds.

    Everyone in the field obviously knows that the “local” p-values vastly overstate the probability that the signal is real. In spite of that, the “actual reasonable” probability that the signal is real may very well be above 50% now.

    • How exactly does one get a posterior probability of signal+background > 50% from this data-set? You’d need some pretty tight priors on the location & width of the signal peak to get those sorts of odds. And from scale of model fitting currently going on, I’d say that was highly unlikely.

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