DELPHES 3, A modular framework for fast simulation of a generic collider experiment

TL;DR

<3-5 sentence high-level summary>

Abstract

The version 3.0 of the DELPHES fast-simulation is presented. The goal of DELPHES is to allow the simulation of a multipurpose detector for phenomenological studies. The simulation includes a track propagation system embedded in a magnetic field, electromagnetic and hadron calorimeters, and a muon identification system. Physics objects that can be used for data analysis are then reconstructed from the simulated detector response. These include tracks and calorimeter deposits and high level objects such as isolated electrons, jets, taus, and missing energy. The new modular approach allows for greater flexibility in the design of the simulation and reconstruction sequence. New features such as the particle-flow reconstruction approach, crucial in the first years of the LHC, and pile-up simulation and mitigation, which is needed for the simulation of the LHC detectors in the near future, have also been implemented. The DELPHES framework is not meant to be used for advanced detector studies, for which more accurate tools are needed. Although some aspects of DELPHES are hadron collider specific, it is flexible enough to be adapted to the needs of electron-positron collider experiments.

Figures (13)

• Figure 1: Left: muon $p_T$ resolution as function of $\eta$ for Delphes and CMS. Right: muon $p_T$ resolution as function of $p_T$ for Delphes and ATLAS. The resolution obtained with Delphes is shown with circular dots and the corresponding statistical uncertainty is shown with vertical error bars, mostly hidden by the dots. For the CMS comparison (left) the band represents the overall (systematic+statistical) uncertainty resulting from the measurement of the muon momentum resolution in CMS data bib:muoncms. For ATLAS (right) the band represents the statistical uncertainty on the resolution obtained in simulation bib:muonatlas.
• Figure 2: Electron and photon energy resolution as a function of the energy for a CMS-like detector. The CMS gaussian electron resolution is from bib:elecms. At high energy, the electron and photon resolutions are driven by ECAL and are therefore identical. At low energy, the electron resolution is largely driven by the superior tracking resolution.
• Figure 3: Left: Comparison of the jet energy resolution of Particle-Flow and Calorimeter jets in CMS bib:pflow and Delphes. Right: Comparison of the jet energy resolution of Calorimeter jets in Delphes and ATLAS bib:jetatlas. The band represents the resolutions obtained with different methods in the ATLAS simulation.
• Figure 4: Left: Particle-Flow $E_T^{miss}$ and Calorimeter $E_T^{miss}$ resolution in Delphes and CMS bib:pflow. Right: $E_{x,y}^{miss}$ resolution in Delphes and ATLAS as a function of the number of reconstructed primary vertices bib:metatlas. The grey band represents the discrepancy between the ATLAS simulation and data.
• Figure 5: Reconstructed hadronic top mass distributions for the correct assignments (left), wrong assignments (centre) and unmatched permutations (right). The Delphes distributions are normalized to the CMS yield. The CMS contributions are taken from ref. bib:ttbarcms.