Litcius/Paper detail

The GAMBIT Universal Model Machine: from Lagrangians to likelihoods

Sanjay Bloor, Tomás E. Gonzalo, Pat Scott, Christopher Chang, Are Raklev, José Eliel Camargo-Molina, Anders Kvellestad, Janina J. Renk, Peter Athron, Csaba Balázs

2021The European Physical Journal C20 citationsDOIOpen Access PDF

Abstract

Abstract We introduce the Universal Model Machine (), a tool for automatically generating code for the global fitting software framework , based on Lagrangian-level inputs. accepts models written symbolically in and formats, and can use either tool along with and to generate model, collider, dark matter, decay and spectrum code, as well as interfaces to corresponding versions of , , and (C "Image missing"). In this paper we describe the features, methods, usage, pathways, assumptions and current limitations of . We also give a fully worked example, consisting of the addition of a Majorana fermion simplified dark matter model with a scalar mediator to via , and carry out a corresponding fit.

Topics & Concepts

GambitDark matterMAJORANAComputer scienceScalar (mathematics)Code (set theory)SoftwareParticle physicsImage (mathematics)Python (programming language)Theoretical computer sciencePhysicsProgramming languageFermionArtificial intelligenceMathematicsSimulationGeometrySet (abstract data type)Computer simulationFluentParticle physics theoretical and experimental studiesDistributed and Parallel Computing SystemsComputational Physics and Python Applications