MC weights for MG @ LO

Asked by Anna Ivina

Dear experts,

I know that the question of MC weights at LO was asked but I wanted to ask a bit more different which confuses me a bit.
If you think it is still the same will you kindly direct me to the answer?
If you think it is irrelevant to ask here also please let me know and sorry for bothering.

I have generated my process of interest as
import model Higgs_Effective_Couplings_UFO
generate p p > h c QED<=1
add process p p > h c~ QED<=1

and then I added in the extras the following things:

extras = { 'lhe_version':'3.0',
           'cut_decays':'F',
           'pdlabel':"'lhapdf'",
           'lhaid' : '260000',
           'parton_shower':'PYTHIA8',
           'use_syst':"True",
           'sys_scalefact':'1.0 0.5 2.0',
           'sys_pdf' : 'NNPDF30_nlo_as_0118',
           'ptj':'10',
           'etaj':'4.7'
          }

According to what I understood adding use_syst = true and sys_scalefact = 1,0.5,2.0 - will get scale and PDF variations via event weights.

I know that at LO the MC weights correspond to the cross-section,
I know that if I would work with Sherpa or Powheg, and I wanted to make any sort of distributions I would use the MC weights,
but as I understand this is not the case in MG_LO since it is just a cross section. And that setup which I used will give me only the weights as systematic variations. Is that true?

Thank you for your help,
Anna

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Olivier Mattelaer (olivier-mattelaer) said :
#1

Hi,

1) I do not know your (CMS?) framework so you might need to adjust stuff
2) For this re-weighting are you using SysCalc or the built-in method?
I consider SysCalc as outdated and lacking the support of many options.
You can contact the authors of that tools to confirm but I believe that they do not have full support
for weight normalisation.

> I know that at LO the MC weights correspond to the cross-section,

3) You can actually choose the normalisation that you want.
you can choose to have event_norm on "sum" or "average"
and this will change the normalisation of the weight to your choice of normalisation.

> but as I understand this is not the case in MG_LO since it is just a cross section. And that setup which I used will give me only the weights as systematic variations. Is that true?

All the systematics weight will follow the same normalisation as the one of the central weight.
You can do plot in the exact same way for those as for the central (assuming that you were using those weights for the central obviously)

Cheers,

Olivier

> On 20 Mar 2019, at 09:03, Anna Ivina <email address hidden> wrote:
>
> New question #679354 on MadGraph5_aMC@NLO:
> https://answers.launchpad.net/mg5amcnlo/+question/679354
>
> Dear experts,
>
> I know that the question of MC weights at LO was asked but I wanted to ask a bit more different which confuses me a bit.
> If you think it is still the same will you kindly direct me to the answer?
> If you think it is irrelevant to ask here also please let me know and sorry for bothering.
>
>
> I have generated my process of interest as
> import model Higgs_Effective_Couplings_UFO
> generate p p > h c QED<=1
> add process p p > h c~ QED<=1
>
> and then I added in the extras the following things:
>
> extras = { 'lhe_version':'3.0',
> 'cut_decays':'F',
> 'pdlabel':"'lhapdf'",
> 'lhaid' : '260000',
> 'parton_shower':'PYTHIA8',
> 'use_syst':"True",
> 'sys_scalefact':'1.0 0.5 2.0',
> 'sys_pdf' : 'NNPDF30_nlo_as_0118',
> 'ptj':'10',
> 'etaj':'4.7'
> }
>
> According to what I understood adding use_syst = true and sys_scalefact = 1,0.5,2.0 - will get scale and PDF variations via event weights.
>
> I know that at LO the MC weights correspond to the cross-section,
> I know that if I would work with Sherpa or Powheg, and I wanted to make any sort of distributions I would use the MC weights,
> but as I understand this is not the case in MG_LO since it is just a cross section. And that setup which I used will give me only the weights as systematic variations. Is that true?
>
> Thank you for your help,
> Anna
>
> --
> You received this question notification because you are an answer
> contact for MadGraph5_aMC@NLO.

Revision history for this message
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#2

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