hh production cross section in SM

Hi,

> as far as we understand "heft" includes only ggh vertex, not gghh.

This is not True the heft model includes also gghh vertex.
Now the Higgs Effective (dimension 5) operator is valid in the infinite top mass limit and
while this is valid for g g > h this is not valid anymore for di-higgs production (since 2 m_h is bigger than the top mass)

At Leading Order the best is to perform the exact loop-induced computation:
import model sm
generate g g > h h [QCD]
(see 1507.00020 <https://arxiv.org/abs/1507.00020>)

For NLO accuracy, this is much more complex. The two loop computation are now available but not within MG5aMC so with our tools you can not achieve full NLO accuracy. What we proposed was to perform the NLO computation with the Effective Operator and then use re-weighting approach to include the mass effect (1401.7340 <https://arxiv.org/abs/1401.7340> and 1607.00763 <https://arxiv.org/abs/1607.00763>)

Cheers,

Olivier

> On 9 Jan 2021, at 20:41, Nurhan Karahan <email address hidden> wrote:
>
> New question #694868 on MadGraph5_aMC@NLO:
> https://answers.launchpad.net/mg5amcnlo/+question/694868
>
> Dear Madgraph team,
>
> We are interested in pp -> hh process. The main contributions to this process comes from gghh effective vertex. We want to check the compatibility of the cross section values of pp->hh process with the values in https://twiki.cern.ch/twiki/bin/view/LHCPhysics/LHCHWGHH?redirectedfrom=LHCPhysics.LHCHXSWGHH (the table in "Latest recommendations for gluon fusion" part).
>
> We obtained a SM model including ggh and gghh vertex for Madgraph via adding these effective vertex to Feynrules SM file. But we did not obtained true cross section values for pp->hh process.
>
> Which model in Madgraph gives these values? as far as we understand "heft" includes only ggh vertex, not gghh.
>
>
> --
> You received this question notification because you are an answer
> contact for MadGraph5_aMC@NLO.

Thank you for your reply,

Actually, we want to use Madgraph for our BSM model. In this case we can use it only at LO for our model.