Flavour break-up July7th 2008 Our aim was modest: 1)To alter fc=0.15 to fc=0.09 following investigations of the charm fraction 2)To take into account the fact that fc will vary with mc and with Q20, when we do our model errors 3)But Joel was doing this with non-dynamic generation and myself with dynamic generation of charm, i.e I ONLY use fc when setting the normalisation of AUbar=ADbar(1-fs)/(1-fc) … the dynamic generation takes car of the amount of charm itself We chose fc=0.09 ± 0.02 for fc model dependence fc=0 at Q20=2 and fc=0.13 at Q20=6 fc=0.06 at mc=1.5 and fc=0.10 at mc=1.35 After having looked at the charm fractions in appropriate jobs.

First to assure you that nothing we have shown the world looks significantly different NEW OLD And obviously the comparisons to CTEQ, MRST/MSTW also look the same.

I have a file of all the plots at different Q2 as shown at DIS2008, Joel has it- nothing looks different H1/ZEUS combined PDFs with total experimental uncertainty plus model uncertainty OLDHERA I PDFs NEWOLD

Now we did not actually show the world how our six model uncertainties affect the uncertainty separately But I have shown it in these meetings, so I did it again with the new fc settings First I looked at uv,dv, Sea, glue and U,D, Ubar Dbar There is NO DIFFERENCE for: mb, fs, Q2min Or for mc: – these model uncertainties are so small that the fact that fc is now changing with mc just doesn’t show up There is a small difference for fc itself which only shows up on the U,D,Ubar,Dbar plot There is also a small difference for Q20, which shows up on the U,D,Ubar Dbar plot….. These two small differences are shown below, the rest are in a file which I sent to Joel.

If you look at flavour break-up U/D you can see that the fc matters less than it did..make a tif file? OLD Include only variation of charm fraction fc: 0.10 →0.20 OLD 0.07 → 0.11 NEW This model dependence is smaller now as it should be! NEW

Include only variation of starting scale Q 0 2 : 2 → 6 GeV 2 Has a small asymmetric effect on PDF ucertainties NEW has slightly smaller model dependence than old- this is also as expected NEW OLD

We also made comparisons of our central fit to some model variations, so this had to be done again These plots also look ALMOST the same But if you look carefully at high-x Dbar- well within the experimental errors, you can see some difference- This is illustrated below for the H1 and ZEUS style parametrizations The complete file was also sent to Joel

Comparison of central fit plus total uncertainties to parametrization variation using: New H1 optimised parametrization OLD/NEW very slightly different at high-x Dbar NEWOLD

NEWOLD Comparison of central fit plus total uncertainties to parametrization variation using: New ZEUS-JETS optimised parametrization OLD/NEW look the same apart from very high-x Dbar

Now consider flavour break-up ubar,dbar cbar, sbar Clearly this is going to be more dependent on our assumptions Remember we have not yet shown this to the world First we ‘ll look at the total model dependence with all model uncertainty Then at break up of this into the 6 different sources

Now there really IS a big new/old difference..where does it come from in detail? (don’t bother looking at the blue lines- that’s another story) OLDNEW All 6 sources

For the variation of fs, new/old the same- as they should NEW OLD Variation of fs

Old had mb and mc -neither made any difference New has JUST mb.. it is no longer true that changing mc gives no model dependence! For variation of mb NEW/OLD are the same NEW OLD Variation of mb

Variation of the Q2 cut NEW/OLD similar- slight difference in cbar NEW OLD Variation of Q2min

Old had mb and mc New haS JUST mc.. it is no longer true that changing mc gives no model dependence! This makes sense. In dynamic generation the amount of charm does change with mc- this is a new source of model error NEW OLD

Variation of fc used to make a difference because it was imposed. But with dynamic generation fc does NOT change the amount of cbar Only the Ubar Dbar relative norm has changed – we CAN’t Agree on this unless we both do it dynamically – this give significantly less model error NEW OLD Variation of fc

Change of Q20 used to affect the flavour break up a lot because fs and fc were not changed accordingly. Now that fs anf fc are changed with Q20, the change of Q20 itself is not a big effect. BUT Joel and I do not agree on this! NEW OLD Change of Q20

However, we know that I am using dynamic generation and he is not.. So I went back and ran jobs for the central value and the Q20 variations Not using dynamic variation and I get the old/new comparsion which I show below OLDNEW I believe this does agree with Joel

Now I have discovered something else interesting about this but before we go on I should just get the question of W/Z predictions out of the way The predictions for W and Z do not look very different but have benefited from a decrease in model errors from using the dynamic method So what I showed the world was conservative. What we are now talking about is whether the improvement is not quite as good as my new plots show

OLD plus 6 model errors NEW plus 6 model errors

OLD plus 6 model errors NEW plus 6 model errors

Back to dynamic vs non-dynamic Those with sharp eyes may have noticed that there was a blue curve on the previous plot of the non- dynamic method and its Q20 variations. This blue curve was a comparison to the dynamic method. Here it is again for our starting scale Q2=4. The dynamic method is generating MORE charm than the non-dynamic method. EVEN though we tried to make it the same by fixing fc to the value that the job seemed to want! Now as I said the dynamic method generates its own amount of charm- We can’t interfere with it. But we can interfere with how much the non-dynamic method has by changing fc

SO I tried to see what fc needed to be in order that the non-dynamic method would generate the same amount as the dynamic method, by the trial and error method- well I actually look at the intercepts of cbar and ubar at x=10^-4, to calculate the fc fraction that dynamic wants- this shouldn’t be as good as integrating the charm fraction and yet it seems to do better Here in red is the dynamic In black is non-dynamic at fc=0.09 Here in red is the dynamic In black is non-dynamic at (guess what?) fc=0.15!!!!!!- oh you clever H1 people!

SO..if you don’t like dynamic- because only I can do it at the moment -or for any other reason, perhaps we should consider going back to non-dynamic at fc=0.15 BUT we should still vary fc with Q20 and with mc according to what the dynamic value would be. Looking at the dynamic job (above), and using the intercepts as before, that would be fc=0.0 at Q20=2, and fc=0.21 at Q20=6

mc=1.4 in black, mc=1.5 in red mc=1.4 in black, mc=1.35 in red And for the mc variations, that would be fc=0.13 for mc=1.5 and fc=0.18 for mc=1.35

I have not had the time to re-do these non-dynamic variants and see if I’m right, and what the model dependence looks like now, but it wouldn’t take long- particularly since much of it is already done if we chose fc=0.15 again. So we have to decide what to do for our first release: Dynamic or non-dynamic? If non-dynamic then go back to central fc=0.15, but with my new suggested values for variations for Q20 and mc? What model dependence on fc itself? Back to 0.10 to 0.20?..I don’t like this, since the dynamic variation gives no model dependence at all! But we can compromise. Also Joel and I have found that he uses mc=1.3 to 1.55 and I have always used 1.35 to 1.5 just need to decide!