I mention this because Tommaso has now produced an animated GIF of the tweaking up of the MC/data Jet energy scale in the CDF analysis, showing how the residues of data minus simulation behave for JES shifts of 0% to 7%. To put this in perspective, you should know that in 2006 CDF published (actually a few physicists from CDF, a dozen of them to be exact, and among them yours truly) an analysis of their Jet energy scale, assessing at 3% the uncertainty on that quantity.

One should also remember that CDF can now verify the agreement of their jet energy scale with simulations to a much better precision than 3%, by fitting the W->jj decay signal in top pair decays when they fit the top quark mass. The current measurements have a precision of 1% on the jet energy scale, in fact. However, one should also consider that the background in the new CDF analysis may be due to gluon-originated jets, which might be subjected to a different jet energy scale with respect to quark-jets that originate in hadronic W boson decays measured in top mass measurements.

In any case, I suggest you to give a look at Tommaso's animated GIF.

## Comments

An off topic, but topical, question: what is the point of a collaboration quoting a 2% confidence level?

See new MINOS paper.

the internal review process did consider these effects, of course. I cannot write more about it here, but if the paper is out it means that CDF considered the JES not a valid explanation of the signal.

About 2% CLs, the point is probably to give something like a p-value for their observation. I do find it kind of twisted myself, but I have not checked the paper yet (I'm on a slow connection right now).

Cheers,

T.

The point is that fitting mixing parameters for the neutrino and anti-neutrino oscillation data independently (4 parameters) yields a better description of the data than a joint fit (2 parameters). The question is how often does this happen by chance when the underlying oscillation parameters are the same for neutrinos and anti-neutrinos? The procedure is to do the 2 parameter fit to the data, then use MC pseudo experiments at that best fit to figure out how often your 4 parameter fit yields a description that is at least as improved (chi2 difference) as what you see when fitting the data with 4 parameters. The answer is that this happens 2% of the time. Hard to boil this down into one pithy sentence.

Sweet lord, that may make the bump go away, but it breaks havoc elsewhere at higher and lower mass: if the purpose of that animated gif was to convince us that this is an artifact of the energy scale, I am afraid the effect on me has been the exact opposite. Besides, it was emphasized several times yesterday that they have a good grip on this scale.

In other words, if I place a cut on jet energies at 20 GeV, say, on data and MC, and then scale up all MC energies by 10%, I do not expect that there will be any events at 20 GeV left in the MC after the procedure. Clear ?

I am more impressed by the better agreement of the W/Z peak after a shift.

Cheers,

T.

Hi Tommaso, thank you for your answer to my question on how this plot was made that I asked at your original post. I wrote a reply there. You confirmed that Tommaso Tabarelli de Fatis made these very nice plots using only the Mjj plot given on the left. For a JES scale increase by 4%, the energy of each jet increases by 4% and the Mjj value increases by 4%. That means that on the graph the MC-based background shape is shifting to the right. However, I have the impression that this works only when you have the values of Mjj on an event by event basis, which again Tommaso Tabarelli de Fatis does not have. Otherwise, he has to assume all the events in the first bin have exactly one value of Mjj and thus the entire bin content should move to another value of Mjj that lives in another bin. Is this what he did? If so, then either all content of the first bin remained in the first bin, or all moved to the second bin. But in his plot only some events from the first bin moved to the second bin. That makes me think that he assumes a distribution of events inside each bin, either a Gaussian distribution or a flat distribution or linear distribution from the value of previous bin to the value of the next bin. If he does that, he can estimate the value of Mjj on an event by event basis. Then he can shift the values of Mjj by 4%. Then he would see each value in which bin it is. And then he would get the new plot. Is this how he did? Is there another way, short of knowing the real values on an event by event basis? I ask as as a student I would like to understand and learn this technique. It can be helpful in the future.

Thanks,

Adrian

I do not know the details of what Tommaso did, but I trust he did things the best way allowed by the data he had. Which could be something of the kind you describe above. I would personally fit the total mass distribution to derive a functional form to get distributions within each bin, but I think these effects are small and beside the point.

In general, there is a better way, which is called "template morphing", to handle these variations. One works with the cumulative distributions instead than with the differential ones, and interpolates those.

Cheers,

T.

Tommaso, something is wrong with your RSS feed. I never get updates anymore, just an error that says your live bookmark failed to load while all my others work fine.

I'm confused. Surely this is something that the CDF review process would cover?