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Benchmarking Hadronic Models in Geant4 for Detector Simulations

S. D. Savenkov, A. O. Svetlichnyi, I. A. Pshenichnov

TL;DR

The paper evaluates how Geant4 hadronic model choices, implemented as HP Reference Physics Lists ($RPL$), affect detector simulations for the HGND prototype in BM@N/NICA. By comparing FTFP_BERT_HP, QGSP_BIC_HP, and QGSP_INCLXX_HP within Geant4 v11.2 across proton/neutron energies of 600 MeV and 3.8 GeV, it analyzes secondary-fragment multiplicities and the resulting scintillator signals. It finds substantial differences in the absorber-stage fragment distributions (notably for Z in the 3–15 range) but a convergence for fragments with Z≤7 reaching scintillators, which mitigates differences in the light signals. The study also quantifies layer-dependent systematic uncertainties (e.g., 19% vs 14% in the first layer for the two energies) and suggests that future work with detailed geometry, trigger modeling, and BM@N data will further constrain detector-performance estimates derived from these models.

Abstract

The construction of modern detectors used in high-energy physics experiments is typically guided by modeling with the Geant4 toolkit to evaluate detector performance in terms of geometrical acceptance and detection efficiency. Several hadronic models are available in Geant4 for modeling nuclear reactions induced by fast nucleons. It is shown that they result in different multiplicity and charge distributions of secondary particles and nuclear fragments. The impact of these differences on modeling the Highly-Granular Neutron Detector (HGND) prototype for the BM@N experiment at Nuclotron-based Ion Collider fAcility (NICA) is evaluated.

Benchmarking Hadronic Models in Geant4 for Detector Simulations

TL;DR

The paper evaluates how Geant4 hadronic model choices, implemented as HP Reference Physics Lists (), affect detector simulations for the HGND prototype in BM@N/NICA. By comparing FTFP_BERT_HP, QGSP_BIC_HP, and QGSP_INCLXX_HP within Geant4 v11.2 across proton/neutron energies of 600 MeV and 3.8 GeV, it analyzes secondary-fragment multiplicities and the resulting scintillator signals. It finds substantial differences in the absorber-stage fragment distributions (notably for Z in the 3–15 range) but a convergence for fragments with Z≤7 reaching scintillators, which mitigates differences in the light signals. The study also quantifies layer-dependent systematic uncertainties (e.g., 19% vs 14% in the first layer for the two energies) and suggests that future work with detailed geometry, trigger modeling, and BM@N data will further constrain detector-performance estimates derived from these models.

Abstract

The construction of modern detectors used in high-energy physics experiments is typically guided by modeling with the Geant4 toolkit to evaluate detector performance in terms of geometrical acceptance and detection efficiency. Several hadronic models are available in Geant4 for modeling nuclear reactions induced by fast nucleons. It is shown that they result in different multiplicity and charge distributions of secondary particles and nuclear fragments. The impact of these differences on modeling the Highly-Granular Neutron Detector (HGND) prototype for the BM@N experiment at Nuclotron-based Ion Collider fAcility (NICA) is evaluated.
Paper Structure (7 sections, 2 figures)

This paper contains 7 sections, 2 figures.

Table of Contents

  1. Introduction
  2. Hadronic models and RPL of Geant4
  3. Detector configuration
  4. Modeling results
  5. Charge distributions of secondary fragments
  6. Signals in scintillator layers
  7. Conclusion

Figures (2)

  • Figure 1: Average multiplicities of secondary fragments produced in all copper absorber layers (top) and of fragments propagated to the adjacent scintillator layers (bottom) calculated with three RPLs for 600 MeV neutrons.
  • Figure 2: Signals in scintillator layers from 600 MeV (top) and 3.8 GeV (bottom) neutrons calculated with three RPLs. The layer number 0 is the VETO layer. Points with error bars represent the mean values of signals calculated with three options and their standard deviations.