TY - JOUR
T1 - The GAMBIT Universal Model Machine
T2 - from Lagrangians to likelihoods
AU - Bloor, Sanjay
AU - Gonzalo, Tomás E.
AU - Scott, Pat
AU - Chang, Christopher
AU - Raklev, Are
AU - Camargo-Molina, José Eliel
AU - Kvellestad, Anders
AU - Renk, Janina J.
AU - Athron, Peter
AU - Balázs, Csaba
N1 - Funding Information:
We thank the rest of the GAMBIT community, in particular Felix Kahlhoefer, for many helpful discussions, and for helping to develop and test GAMBIT over a period of many years. We also acknowledge PRACE for awarding us access to Marconi at CINECA, Italy, and Joliot-Curie at CEA, France. This project was also undertaken with the assistance of resources and services from the National Computational Infrastructure, which is supported by the Australian Government. We thank Astronomy Australia Limited for financial support of computing resources. Computations were also performed on resources provided by UNINETT Sigma2, the National Infrastructure for High Performance Computing and Data Storage in Norway, under project nn9284k. TEG is supported by DFG Emmy Noether Grant no.?KA 4662/1-1. PS is supported by the Australian Research Council (ARC) under Grant FT190100814. JECM is supported by the Carl Trygger Foundation through grant no. CTS 17:139. JJR acknowledges support by Katherine Freese through a grant from the Swedish Research Council (Contract no. 638-2013-8993). PA, CB and TEG are supported by the ARC under Grant DP180102209. The work of PA was also supported by the Australian Research Council Future Fellowship Grant FT160100274.
Funding Information:
We thank the rest of the GAMBIT community, in particular Felix Kahlhoefer, for many helpful discussions, and for helping to develop and test GAMBIT over a period of many years. We also acknowledge PRACE for awarding us access to Marconi at CINECA, Italy, and Joliot-Curie at CEA, France. This project was also undertaken with the assistance of resources and services from the National Computational Infrastructure, which is supported by the Australian Government. We thank Astronomy Australia Limited for financial support of computing resources. Computations were also performed on resources provided by UNINETT Sigma2, the National Infrastructure for High Performance Computing and Data Storage in Norway, under project nn9284k. TEG is supported by DFG Emmy Noether Grant no. KA 4662/1-1. PS is supported by the Australian Research Council (ARC) under Grant FT190100814. JECM is supported by the Carl Trygger Foundation through grant no. CTS 17:139. JJR acknowledges support by Katherine Freese through a grant from the Swedish Research Council (Contract no. 638-2013-8993). PA, CB and TEG are supported by the ARC under Grant DP180102209. The work of PA was also supported by the Australian Research Council Future Fellowship Grant FT160100274.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12/15
Y1 - 2021/12/15
N2 - 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[InlineMediaObject not available: see fulltext.]). 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.
AB - 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[InlineMediaObject not available: see fulltext.]). 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.
UR - https://www.scopus.com/pages/publications/85121401086
U2 - 10.1140/epjc/s10052-021-09828-9
DO - 10.1140/epjc/s10052-021-09828-9
M3 - Article
AN - SCOPUS:85121401086
SN - 1434-6044
VL - 81
JO - European Physical Journal C
JF - European Physical Journal C
IS - 12
M1 - 1103
ER -