GATE 10 Monte Carlo particle transport simulation

II. Architecture and innovations

Journal Article (2026)
Author(s)

Nils Krah (HollandPTC, Université de Lyon)

Nicolas Arbor (University of Strasbourg)

Thomas Baudier (Université de Lyon)

Julien Bert (University of Brest/INSERM/LaTIM)

Konstantinos Chatzipapas (University of Brest/INSERM/LaTIM, TU Delft - RST/Applied Radiation & Isotopes)

Martina Favaretto (MedAustron Ion Therapy Center)

Hermann Fuchs (Medical University of Vienna)

Loïc Grevillot (MedAustron Ion Therapy Center)

Hussein Harb (University of Brest/INSERM/LaTIM)

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Research Group
RST/Applied Radiation & Isotopes
DOI related publication
https://doi.org/10.1088/1361-6560/ae237c
More Info
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Publication Year
2026
Language
English
Research Group
RST/Applied Radiation & Isotopes
Journal title
Physics in medicine and biology
Issue number
1
Volume number
71
Article number
015043
Downloads counter
6
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Abstract

Over the past years, we have developed GATE version 10, a major re-implementation of the long-standing Geant4-based Monte Carlo application for particle and radiation transport simulation in medical physics. This release introduces many new features and significant improvements, most notably a Python-based user interface replacing the legacy static input files. The new functionality of GATE version 10 is described in the part 1 companion paper (Sarrutet al2025 arXiv:2507.09842). The development brought significant challenges. In this paper, we present the solutions that we have developed to overcome these challenges. In particular, we present a modular design that robustly manages the core components of a simulation: particle sources, geometry, physics processes, and data acquisition. The architecture consists of integrated C++ and Python codes. This framework allows for the precise, time-aware generation of primary particles, a critical requirement for accurately modeling positron emission tomography, radionuclide therapies, or prompt-gamma timing systems. We present how GATE 10 handles complex Geant4 physics settings while exposing a simple interface to the user. Furthermore, we describe the methodological solutions that facilitate the seamless integration of advanced physics models and variance reduction techniques. The architecture supports sophisticated scoring of physical quantities (such as Linear Energy Transfer and Relative Biological Effectiveness) and is designed for multithreaded execution. The new user interface allows researchers to script complex simulation workflows and directly couple external tools, such as artificial intelligence models for source generation or detector response. By detailing these architectural innovations, we demonstrate how GATE 10 provides a more powerful and flexible tool for research and innovation in medical physics. This paper is not intended to be a developer guide. Its purpose is to share with the research community in-depth explanations of our development effort that made the new GATE 10 possible.