PineAPPL Grids of Open Heavy-Flavor Production in the GM-VFNS
Jan Wissmann, Tom\'a\v{s} Je\v{z}o, Ingo Schienbein, Hubert, Spiesberger, Michael Klasen

TL;DR
This paper presents the creation of PineAPPL grids for open heavy-flavor production in the GM-VFNS, enabling fast and accurate predictions for QCD analyses by interpolating Monte Carlo results.
Contribution
The work introduces PineAPPL grids for GM-VFNS heavy-flavor production, improving computational efficiency without sacrificing accuracy in QCD predictions.
Findings
Achieved better than permille agreement between grids and MC predictions.
Significantly reduced computation time for predictions in global PDF analyses.
Validated the grid approach across different kinematic regions.
Abstract
Many next-to-leading order QCD predictions are available through Monte Carlo (MC) simulations. Usually, multiple CPU hours are needed to calculate predictions at a required precision, which is unfeasible for global PDF analyses. This problem is solved by a process known as gridding: The values of the hard-scattering cross-section are calculated only once with the MC program, and then interpolated and stored in look-up tables (grids) of the kinematical variables. To obtain the physical predictions, they are convolved with the PDFs (e.g. during the fitting stage in a PDF global analysis), which takes a tiny fraction of the time needed to calculate the MC results. This is possible with PineAPPL, a library tackling the aforementioned process of grid creation and convolution. In this work, we use PineAPPL to grid the predictions for open heavy-flavor production in the general-mass…
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