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matclim edited this page Dec 15, 2025 · 3 revisions

FairShip Documentation

Introduction

  • Purpose of the FairShip
  • Scope and intended use
  • High-level architecture

Installation

  • System requirements
  • Dependencies
  • Build and installation procedure
  • Environment setup
  • Validation and testing
  • Data formats

Subsystems

Target Complex

  • Overview
  • Geometry and materials
  • Interfaces

Magnet System

  • Overview
  • Magnetic field modeling

Scattering Neutrino Detector

  • Overview
  • Detector layout
  • Readout and reconstruction

Upstream Background Tagger

  • Overview
  • Tagging strategy

Surround Background Tagger

  • Overview
  • Coverage and acceptance

Spectrometer

  • Overview
  • Tracking and momentum reconstruction

Timing Detector

  • Overview
  • Time resolution

PID Systems

  • Overview

The PID systems encompass two separate detectors: an ECAL, the SplitCal and an HCAL. The ECAL is composed of three separate subsystems, two of which are implemented in FairSHiP: 6cm wide scintillator bars and High Precision Layers (HPLs). Thin (1cm) scintillator bars are also planned for the ECAL but are not present in FairSHiP at this time. A simulation prototype using DD4HEP which includes a more complete PID system can be found here: https://github.com/matclim/DD4SHiP

The information relative to the SplitCal is contained in the relevant directory (splitcal). The HCAL is to be merged, developments can be followed here: https://github.com/matclim/FairShip.

  • Particle identification methods

PID was done using both cuts and using multivariate analysis using older versions of FairSHiP and the newer, DD4HEP prototype. Indicative performance using BDTs can be found below:

image
  • Performance metrics

The SplitCal has four primary roles in the SHiP apparatus: enhance particle identification, reject background, measure the energy of photons and (anti-)electrons as well as provide tracking and vertexing for neutral final states thanks to its excellent angular resolution.

The performance metrics as currently envisaged are thus as follows:

For particle identification, a measure of the diagonality of the confusion matrix (difference in Frobenius norms)

For background rejection, a dedicated study with metrics to be determined

The energy resolution calibration

Tracks: track resolution as a function of particle energy

Vertex: vertex resolution as a function of track energy and true vertex location.

Analysis

Simulation

  • Description

Muon DIS Background

  • Description
  • Simulation and modeling
  • Rejection strategies

Neutrino Background

  • Sources
  • Event characteristics
  • Mitigation approaches

Muon Combinatorial Background

  • Origin
  • Reconstruction ambiguities
  • Suppression techniques

Appendix (Optional)

  • Configuration files
  • Glossary

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