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The GAMBIT Universal Model Machine: from Lagrangians to Likelihoods

Authors :
Bloor, Sanjay
Gonzalo, Tomás E.
Scott, Pat
Chang, Christopher
Raklev, Are
Camargo-Molina, José Eliel
Kvellestad, Anders
Renk, Janina J.
Athron, Peter
Balázs, Csaba
Source :
Eur. Phys. J. C 81, 1103 (2021)
Publication Year :
2021

Abstract

We introduce the GAMBIT Universal Model Machine (GUM), a tool for automatically generating code for the global fitting software framework GAMBIT, based on Lagrangian-level inputs. GUM accepts models written symbolically in FeynRules and SARAH formats, and can use either tool along with MadGraph and CalcHEP to generate GAMBIT model, collider, dark matter, decay and spectrum code, as well as GAMBIT interfaces to corresponding versions of SPheno, micrOMEGAs, Pythia and Vevacious (C++). In this paper we describe the features, methods, usage, pathways, assumptions and current limitations of GUM. We also give a fully worked example, consisting of the addition of a Majorana fermion simplified dark matter model with a scalar mediator to GAMBIT via GUM, and carry out a corresponding fit.<br />Comment: 32 pages, 6 figures, 3 tables

Details

Database :
arXiv
Journal :
Eur. Phys. J. C 81, 1103 (2021)
Publication Type :
Report
Accession number :
edsarx.2107.00030
Document Type :
Working Paper
Full Text :
https://doi.org/10.1140/epjc/s10052-021-09828-9