FairShip is the official software framework for the SHiP (Search for Hidden Particles) experiment at CERN, built on top of FairRoot and tightly integrated with ROOT and Geant4. It provides everything needed to take a physics process from an event generator through a full Geant4 detector simulation, digitisation, track reconstruction, and analysis — all within a single coherent package. Because SHiP targets an extraordinary range of feebly-interacting particles, the framework has been designed to accommodate multiple generator backends, configurable detector geometries, and both established and experimental reconstruction algorithms.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/ShipSoft/FairShip/llms.txt
Use this file to discover all available pages before exploring further.
The SHiP Experiment
SHiP is a beam-dump experiment proposed for CERN’s ECN3 facility. A high-intensity 400 GeV proton beam strikes a dense target, producing an enormous flux of charm and beauty hadrons. Hidden particles — such as Heavy Neutral Leptons (HNLs) and dark photons — can be produced in those decays and then travel through a substantial hadron absorber before entering a dedicated decay volume instrumented with tracking detectors, calorimetry, and timing systems. The experiment is specifically optimised to discover particles with extremely small couplings to the Standard Model that have so far escaped detection at collider experiments.Software Components
FairShip bundles a complete chain of simulation and analysis tools:Event Generators
Pythia6, Pythia8, EvtGen, and GENIE for neutrino interactions; EventCalc for importing pre-generated signal samples; a configurable particle gun (
PG sub-command) for detector studies.Geant4 Detector Simulation
Full GEANT4-based transport of particles through the SHiP detector geometry, including magnetic fields, sensitive detectors, and optional VMC back-ends via Geant4-VMC.
Analysis Toolkit
ShipAna.py provides a reference analysis script, while the analysis_toolkit module offers a pre-selection framework. ShipAna accesses MC truth and reconstruction data simultaneously via ROOT friend trees.Repository Branches
The FairShip repository on GitHub contains several long-lived branches targeting different use cases:| Branch | Purpose | Python | aliBuild default |
|---|---|---|---|
master | Main development branch — all active work happens here | Python 3 (required) | release |
charmdet | Charm cross-section measurement; kept as reference for future studies | — | — |
SHiP-2018 | Frozen snapshot for the CERN CDS, preserved for backward compatibility | Python 2 only | fairship-2018 |
muflux | Muon flux analysis branch | Python 2 only | fairship-2018 |
Active development targets the
master branch exclusively. Python 2 is no longer supported on master. If you are starting new work, always clone master.Class Reference
An automatic C++ class reference is generated from Doxygen comments in the source code and published at https://shipsoft.github.io/FairShip/. Improving inline comments in the C++ source directly improves this documentation for all users.Where to Go Next
Installation
Set up FairShip on lxplus with CVMFS, using pixi on any Linux machine, or via a fully local aliBuild.
Quickstart
Run your first simulation, reconstruction, and analysis in minutes with the standard macro chain.
Simulation Overview
Understand detector geometry configuration, generator options, and Geant4 transport settings.
Reconstruction Overview
Learn how digitisation, pattern recognition with GenFit, and the experimental ACTS pipeline work.