Geant4 Toolkit Research Articles

Non-destructive Elemental Analysis of Lunar Materials with Negative Muon Beam at J-PARC

In the last decade, non-destructive elemental analysis using negative muon beams advanced significantly. This method can be used to determine the elemental composition of bulk materials without causing damage. In this study, we performed a negative muon irradiation experiment for a Northwest Africa 482 lunar meteorite (NWA482), which was installed in a stainless steel analysis chamber. The analysis chamber was filled with helium gas to suppress the background signals caused by air-scattering muons. The muonic X-rays from Al, Fe, Ca, Mg, Si, and O in the samples were detected using six high-purity germanium semiconductor detectors arranged around the analysis chamber. To correct the X-ray self-absorption effect of the samples, a Monte-Carlo simulation using Geant4 toolkit was used. Based on the quantitative analysis for muonic X-ray measurement with the correction application from the simulation, we successfully investigated the analytical sensitivity of each element in meteorites based on the NWA482 data.

A GEANT4 based simulation framework for the large area muon telescope of the GRAPES-3 experiment

The GRAPES-3 experiment located in Ooty, India, samples the electron and muon components in extensive air showers using an array of plastic scintillator detectors and a muon telescope (G3MT) consisting of proportional counters to study the composition of primary cosmic rays (PCRs) as well as γ-ray sources in the TeV–PeV energy range. The G3MT is designed with an appropriate mass absorber to shield the electromagnetic and hadronic components in the shower and to detect muons above 1 GeV×sec(θ) energy, incident from a zenith angle θ. We developed a simulation framework based on the GEANT4 toolkit to evaluate the response of shower particles such as muons, γ-rays, electrons and hadrons in the G3MT. We discuss the geometric modeling of the G3MT using GEANT4 starting with the proportional counter. We estimated the punch-through contribution of hadrons in the G3MT. We compare the simulated muon multiplicity distributions with the observed ones assuming PCR composition from a four population supernova remnant acceleration model namely H4a.

Adding the X‐ray Bragg reflection physical process in crystal to the Geant4 Monte Carlo simulation toolkit, part I: reflection from a crystal slab

AbstractX‐ray diffraction from a solid crystal shows the wave nature of photons. It is an important electromagnetic (EM) physics process when X‐ray photons interact with a crystal. Bragg diffraction, often called Bragg reflection, is a special case of the general form of X‐ray diffraction, known as Laue diffraction. When the Bragg's law is met, the incident photon beam is reflected from the crystal plane behaving as a specular reflection at the Bragg angle. However, the Bragg reflection physical process has not been integrated into the general‐purpose Monte Carlo simulation toolkit Geant4 for particle physics. In the current study, we developed a new EM physical process class “G4CrystalBraggReflection” and a new EM physical model class “G4DarwinDynamicalModel” for modeling the Bragg reflection physical process within a crystal. We added the Bragg reflection physical process to the EM physics category of Geant4. The preliminary results of photon tracking in a silicon crystal slab have shown the feasibility of simulating the Bragg reflection process in addition to the standard EM processes in the framework of Geant4.

MRADSIM-Converter: A new software for STEP to GDML conversion

Radiation effects analysis of instruments operative in harsh radiation environment is crucial for performance and functionality of electronic devices and components. Engineering design of instruments is usually carried out in Computer Aided Design (CAD) engineering software. Geant4-based Monte Carlo codes are extensively used for particle transport simulation and analysis. However, Geant4 is not prepared to accept CAD Standard for The Exchange of Product data (STEP) format. MRADSIM-Converter is a new software for STEP to Geometry Description Markup Language (GDML) format conversion, readable by Geant4-based Monte Carlo codes. Its validation with two different converters confirms its higher speed for importing CAD geometries with arbitrary size and complexity having a user-friendly interface for modifying volumes properties. Program summaryProgram title: MRADSIM-ConverterCPC Library link to program files:https://doi.org/10.17632/8kzsyn79gh.1Licensing provisions: LGPLProgramming language: C++Supplementary material: CMake, Qt5, OpenCascadeNature of problem: Geant4 toolkit simulation code developed at CERN is widely used for high energy physics community as well as health physics and radioprotections communities. However, Geant4 is not prepared to receive the CAD formats file, and the geometry implementation in Geant4 is a time-consuming task as it requires the creation of each volume using specific classes.Solution method: MRADSIM-Converter is a software designed to perform a conversion between the files written in STEP format, prepared by CAD software, into the GDML format, accepted as input in Geant4. All existent volumes in the input STEP file are visualized in the Graphical User Interface (GUI), where it is possible to interactively assign the material to the components and modify each volume's properties, such as material, color, and name.Additional comments including restrictions and unusual features: MRADSIM-Converter is tested under Ubuntu, versions 18 and 20. All the libraries necessary to run the program are provided in the package hence no additional library or software is required to be installed. Under MacOS and Windows, MRADSIM-Converter is running through virtual machine (VM) with above-mentioned Ubuntu versions.

Meta-learning for multiple detector geometry modeling

The simulation of the passage of particles through the detectors of High Energy Physics (HEP) experiments is a core component of any physics analysis. A detailed and accurate simulation of the detector response using the Geant4 toolkit is a time and CPU consuming process. With the upcoming high luminosity LHC upgrade, with more complex events and a much increased trigger rate, the amount of required simulated events will increase. Several research directions investigated the use of Machine Learning based models to accelerate particular detector response simulation. This results in a specifically tuned simulation and generally these models require a large amount of data for training. Meta learning has emerged recently as fast learning algorithm using small training datasets. In this paper, we propose a meta-learning model that “learns to learn” to generate electromagnetic showers using a first-order gradient based algorithm. This model is trained on multiple detector geometries and can rapidly adapt to a new geometry using few training samples.

Fully Geant4 compatible package for the simulation of Dark Matter in fixed target experiments

A package for the simulation of Dark Matter (DM) particles is presented. It is intended for fixed target experiments. We chose the Geant4 toolkit framework as a standard in order to be compatible with particle tracking programs used in many High Energy Physics (HEP) experiments. One part of the package is a collection of codes that return the cross sections of DM particles’ production in such processes as electron and muon bremsstrahlung off nuclei, annihilation in flight and Primakoff processes. In most cases they are calculated at runtime. In the case of bremsstrahlung processes the total cross sections are either calculated numerically at exact tree level (ETL) or calculated at runtime using approximations validated by comparing with results of the ETL calculations. Other parts contain codes for the simulation of the above mentioned processes and DM particle classes.

Theoretical consideration of isomeric ratios in some photonuclear reactions induced by bremsstrahlung with endpoint energy in giant dipole resonance region using Talys 1.95 code

Isomeric ratios of isomeric pairs produced by photonuclear reactions (γ, n) on Se, Ce, Eu and Hg targets induced by bremsstrahlung with endpoint energies in the giant dipole resonance region have been theoretically calculated using TALYS 1.95 code in combination with Geant4 simulation. The computed isomeric ratios as a function of the bremsstrahlung endpoint energies in the range of 10 to 25 MeV resulted from convolution between calculated differential cross-sections using six level density models available in TALYS 1.95 and the bremsstrahlung spectra simulated by the GEANT4 toolkit. Moreover, for each level density model, eight gamma strength functions have been employed. The calculated results are compared to the experimental data in the existing literature for Talys 1.95 model evaluation.

Cosmogenic radionuclides in the Cavezzo meteorite: Gamma-ray measurement and detection efficiency simulations

The Cavezzo meteorite was recovered on January 4th, 2020, just three days after the fall observed over Northern Italy by the all-sky cameras of the Italian PRISMA fireball network. Two specimens, weighing 3.1 g (F1) and 52.2 g (F2), were collected in the predicted strewn-field and the meteorite has been classified as an L5 anomalous chondrite. The gamma-activity of the F2 sample was measured at the Monte dei Cappuccini underground Research Station (Torino, Italy) with a large-volume HPGe-NaI(Tl) spectrometer. Thanks to the high efficiency, selectivity, and low background of the spectrometer, we were able to detect fifteen cosmogenic radioisotopes. The presence of nuclides with half-lives down to a few days (47Ca, 52Mn, and 48V) undoubtedly confirmed the recent fall of the sample. The very low activity of 44Ti and 60Co was revealed with a particular coincidence between the HPGe and NaI(Tl) detectors. To obtain the detection efficiency, we have simulated the response of the detector with the GEANT4 toolkit, once the spectrometer’s dead layer thickness was estimated using standards of known activity. Moreover, the simulation of the Dhajala meteorite (H3/4 chondrite) measurement allowed us to verify that the self-absorption of the sample is correctly taken into account and validate our simulations. In this contribution, we focus on the coincidence optimization techniques and the detection efficiency computation.

Detection efficiency calibration for an array of fourteen HPGe detectors

The CUP array of germanium (CAGe) is an array of fourteen high-purity germanium (HPGe) detectors. The detection efficiency of full-energy-peak emitted from the various samples assayed on the CAGe was calculated using the Monte Carlo simulation toolkit GEANT4. If the dead layer on the surface of the crystal is treated in the simulation as a continuous part of the active crystal, then the detection efficiency will be overestimated. Thus, the detection efficiency of the CAGe was adjusted using multi-nuclide source data and Monte Carlo simulations. The gamma spectra of the known activity source were obtained for each HPGe detector of the CAGe. The detection efficiency measured by the multi-source data was smaller than that of simulation data if the simulation treated the whole volume of germanium crystals as active for gamma detection. By optimizing the dead layers’ thicknesses in the simulation, the detection efficiency calculated by the simulation could be matched to that of multi-source data.

Cobalt compensator-based IMRT device: A treatment planning study of head and neck cases

PurposeOur goal is to develop a novel cobalt-compensator-based IMRT device for low- and middle-income countries that is reliable and cost-effective while delivering treatment plans of equal quality to those from linac-MLC devices. The present study examines the quality of treatment plans using this device. MethodsA commercial treatment planning system (TPS; RayStation v.8B) was commissioned for this device using Monte Carlo simulations from the Geant4 toolkit. Patient-specific compensators were created as regions-of-interest. Thirty clinical head & neck cases were planned and compared to clinical plans with a 6MV linac using IMRT. The mock head and neck plan from TG-119 was used for further validation. ResultsPTV objectives were achieved in all 30 plans with PTV V95% >95 %. OAR sparing was similar to clinical plans. There were 14 cases where OAR dose limits exceeded the recommended QUANTEC limits in the clinical plan in order to achieve target coverage. OAR sparing was better in the cobalt compensator plan in 8 cases and worse in 3 cases, in the latter cases exceeding the clinical plan doses by an average of 8.22 % (0.0 %–13.5 %). Average field-by-field gamma pass-rate were 93.7 % (2 %/2mm). Estimated treatment times using the Co-60 compensator device were 1 min 27 s vs 1 min 2 s for the clinical system. ConclusionThis system is the first of its kind to allow for IMRT with a Co-60 device. Data here suggests that the delivery meets plan quality criteria while maintaining short treatment times which may offer a sustainable and cost-low option for IMRT on the global scale.

Accuracy of three-dimensional proton imaging of an inertial confinement fusion target assessed by Geant4 simulation

The Geant4 toolkit was used to perform benchmark Monte Carlo simulations of proton micro-tomography imaging. A phantom of an inertial confinement fusion (ICF) target was designed, based on experimental data. Simulations of STIM (Scanning Transmission Ion Microscopy) and PIXE (Particle Induced X-ray Emission) tomography were performed. Quantitative images were obtained from the TomoRebuild and JPIXET software packages, chosen for their ability to handle large solid angles of X-ray detection. The tomographic images were compared with the original phantom, used as a reference. For STIM-T, the accuracy of the calculated mass density was ≤ 2 % for TomoRebuild and ≤ 14 % for JPIXET. Corrections of X-ray production cross section and X-ray absorption were tested for the quantification of Ge, used as a dopant in the ICF target. The accuracy on the obtained Ge density was ≤ 2.9 % for TomoRebuild and ≤ 6.4 % for JPIXET, whereas the error was about 40 % without correction.

Sensitivity of secondary particle emission to hadronic physics models in GATE/Geant4 proton therapy simulations at 100 MeV

Introduction: Proton therapy simulations rely on Monte Carlo techniques, such as the GATE code based on the Geant4 toolkit, to predict dose distribution and secondary particle production. The accuracy of these simulations is heavily influenced by the chosen physics models. Methods: In this study, we analyzed three Geant4 hadronic physics models, BIC, BERT, and INCL++, by calculating the angular and energy distributions of secondary neutrons and gamma particles. We conducted GATE/Geant4 simulations on a water phantom irradiated with a 100 MeV proton beam. Results: Our investigation revealed notable differences in the angular and energy distributions of emitted particles among the three models. Conclusion: This study emphasizes the necessity of carefully selecting a hadronic physics model for GATE/Geant4 simulations in proton therapy.

Application of machine learning in cosmic ray particle identification

Machine learning algorithms can learn the rules and patterns of big data through computers, excavate potential information hidden behind the data, and be widely used to solve classification, regression, clustering, and other problems. Firstly, this paper uses CORSIKA software to simulate the process of cosmic ray cascade shower in the atmosphere, generating information such as the initial energy, zenith angle, azimuth angle of cosmic ray particles. Then, this paper uses the Geant4 toolkit to conduct thermal neutron detector response simulation, generating 4000 particles in each of proton, helium, CNO, MgAlSi and iron. Based on the experimental simulation data of thermal neutron detector, this paper constructs machine learning models for identifying cosmic ray particles by using decision tree (DT), random forest (RF) and BP neural network (BP NN) respectively. For each particle, all the machine learning algorithms are used for model training based on the simulation data. The cross grid search method is used to adjust the hyper parameters of each machine learning algorithm. The AUC value and <i>Q</i> quality factor value of each algorithm are used as evaluation indexes for particle composition identification. The AUC value is a general indicator for evaluating algorithm performance in machine learning and the <i>Q</i> quality factor value is an evaluation index commonly used in the field of high energy physics. The Experimental results show that different machine learning models have great influence on particle prediction accuracy, and the random forest cosmic ray particle identification model has sufficient accuracy and generalization capability. In the test, the decision tree algorithm adjusted by cross grid search method is sensitive to the medium components (CNO and MgAlSi). The AUC values of the algorithm are all above 0.95 and the <i>Q</i> quality factor values are all above 6. The random forest algorithm adjusted by the cross grid search method has the best effect on the identification of cosmic ray particles. The AUC values of the algorithm are all more than 0.92 and the <i>Q</i> quality factor values are all more than 4. The BP neural network algorithm is only sensitive to proton and iron. This study provides a new method and selection for identifying and screening the cosmic ray particles and it also provides a new idea for the following measurement of cosmic ray energy spectrum by thermal neutron detector.

Quantitative Elemental Analysis Using Whole Spectral Information (with GA and MLR Methods) of Proton Induced Prompt Gamma-Rays Simulated Using Geant4 Toolkit

Purpose: Online determination of the elemental composition of tissues near the Bragg peak is a challenge in proton therapy related studies. In the present work, an analysis method based on the whole spectral information is presented for the quantitative determination of the elemental composition (weight %) of an irradiated target from its emitted Prompt Gamma (PG) spectrum.
 Materials and Methods: To address this issue, four test phantoms with different weights (%) of 12C, 16O, 20Ca, and 14N elements were considered. The simulated PG spectra were recorded using 3 × 3 inch NaI detectors. A library consisting of the spectra of single-element phantoms as well as the spectra of test-irradiated phantoms was produced for 30, 70, and 150 MeV incident protons using the Geant4 Monte Carlo toolkit. The elemental analysis was performed using the information of the whole spectrum by applying two methods, including the well-known Genetic Algorithm (GA) and Multiple Linear Regression (MLR).
 Results: The results show that the proposed method estimates the oxygen concentration accurately. Furthermore, the estimated weights of other elements, with both methods, agree well with nominal values in each test phantom, for the considered energies.
 Conclusion: The proposed quantitative elemental analysis of proton-bombarded phantoms using their induced PG spectrum is expected to be beneficial in treatment planning and treatment verification studies.

Particle identification with the cluster counting technique for the IDEA drift chamber

IDEA (Innovative Detector for an Electron–positron Accelerator) is a general-purpose detector concept, designed to study electron–positron collisions in a wide energy range in a very large circular leptonic collider. Its drift chamber is designed to provide an efficient tracking, a high precision momentum measurement and an excellent particle identification by exploiting the application of the cluster counting technique. To investigate the potential of the cluster counting techniques on physics events, a simulation of the ionization cluster generation is needed, therefore we developed an algorithm which can use the energy deposit information provided by the Geant4 toolkit to reproduce, in a fast and convenient way, the cluster number and cluster size distributions. The results obtained confirm that the cluster counting technique allows to reach a resolution two times better than the traditional dE/dx method. A beam test has been performed during November 2021 at CERN on the H8 beam line to validate the simulations results, to define the limiting effects for a fully efficient cluster counting and to count the number of electron clusters released by an ionizing track at a fixed βγ as a function of the track angle. The simulation and the beam test results will be described briefly in this issue.

Development of a GAGG(Ce)-based compact 3D scanning setup for assessment of active volume in [formula omitted]-ray detectors

A Ce-doped GAGG (Gadolinium Aluminum Gallium Garnet: Gd3Al2Ga3O12) scintillator crystal has been coupled with a multianode position sensitive photomultiplier tube (PSPMT). The system is made compact by employing an external resistive network that reduces the 64 readouts of the PSPMT to only four signals. The resulting GAGG(Ce)-PSPMT setup has been put to use for quick scanning of γ-ray detectors by reconstructing the image of the latter with coincident photons between the pair of detectors. In the present work, such scans are demonstrated for an old single-crystal coaxial reverse-electrode HPGe detector as well as an old clover HPGe detector. For the single-crystal HPGe, the growth of the effective depleted region under increasing reverse-bias voltages has been visualized from the image reconstruction. The active volume is seen to grow from the surface towards the axial cavity. For the clover HPGe detector, dysfunctional portions in the crystals could be identified. The experimental results are found to agree well with simulation carried out using the GEANT4 toolkit. Scanning a detector using this method is faster compared to the scanning process by a point source.

Monte Carlo GEANT4 Simulation Approach in Analyzing Radiation Shielding Parameter of Lombok Pumice

The linear attenuation coefficient (LAC), mean free path (MFP), half-value layer (HVL), and the radiation protection efficiency (RPE) parameters of Lombok pumice powder from 3 different regions (Ijobalit, Setangi beach, and Lingsar) have been analyzed. The radiation parameter analysis was carried out to determine the pumice that potential as a raw material of radiation shielding composite. The Monte Carlo simulation using the GEANT4 toolkit was applied to analyze those parameters using a gamma-ray transmission measurement for the photon energies of 57Co, 133Ba, 54Mn, 137Cs, 60Co, 65Zn, 22Na and 40K. The GEANT4 simulation results were compared to the XCOM theoretical calculation and show that the linear attenuation coefficient parameter has a good agreement with the XCOM results based on the determination coefficient of the correlation graph (R2 = 0.998) between those 2 approaches methods. Setangi beach pumice has a smaller LAC parameter than Ijobalit pumice and Lingsar pumice. The MFP and HVL parameter of the Setangi beach pumice indicate the absorption ability of gamma photons is low. In the low gamma energy 0.122 MeV, Ijobalit pumice and Lingsar pumice have more than 50 % RPE and are better used as a raw material of radiation shielding composite.
 HIGHLIGHTS
 
 New lead-free shielding materials of radiation becomes a critical concern in the investigation of raw shielding material
 GEANT4 Monte Carlo simulation and XCOM theoretical calculation was conducted to analyse the radiation LAC parameter
 Radiation parameters analysis of Lombok Pumice show that Ijobalit pumice and Lingsar pumice have more than 50 % RPE and are better used as a raw material of radiation shielding composite
 
 GRAPHICAL ABSTRACT

A Comparison of Neural Networks and Center of Gravity in Muon Hit Position Estimation.

The performance of cosmic-ray tomography systems is largely determined by their tracking accuracy. With conventional scintillation detector technology, good precision can be achieved with a small pitch between the elements of the detector array. Improving the resolution implies increasing the number of read-out channels, which in turn increases the complexity and cost of the tracking detectors. As an alternative to that, a scintillation plate detector coupled with multiple silicon photomultipliers could be used as a technically simple solution. In this paper, we present a comparison between two deep-learning-based methods and a conventional Center of Gravity (CoG) algorithm, used to calculate cosmic-ray muon hit positions on the plate detector using the signals from the photomultipliers. In this study, we generated a dataset of muon hits on a detector plate using the Monte Carlo simulation toolkit GEANT4. We demonstrate that two deep-learning-based methods outperform the conventional CoG algorithm by a significant margin. Our proposed algorithm, Fully Connected Network, produces a 0.72 mm average error measured in Euclidean distance between the actual and predicted hit coordinates, showing great improvement in comparison with CoG, which yields 1.41 mm on the same dataset. Additionally, we investigated the effects of different sensor configurations on performance.

Design and simulation of a MPGD-based hadronic calorimeter for Muon Collider

The project of a Multi-TeV Muon Collider represents a unique opportunity to explore the high energy physics frontier and to measure with high precision the Higgs coupling with the other particles of the Standard Model as well as the trilinear and quadrilinear Higgs self-coupling, leading to a precise determination of the Higgs potential, in order to confirm the theoretical predictions of the SM and possibly to find evidences for new physics. One of the major challenges for the design and optimization of the technologies suitable for a Muon Collider experiment is represented by the high background induced by the decay of the muons coming from the beam. This contribution present the design of an innovative MPGD-based hadronic calorimeter (HCAL). The detector consists of a sampling calorimeter exploiting the Micro Pattern Gas Detectors (MPGDs) as active layers: MPGDs offer a fast and robust technology for high radiation environments and a high granularity for precise spatial measurements. Moreover, the detector is designed to optimize the jet reconstruction and for background suppression. The calorimeter is simulated using the Geant4 toolkit to support the detector R&D. The detector design and layout optimization supported by the simulation is described.

Calculating the maximum possible yield for a typical pyroelectric neutron generator

Pyroelectric crystals are heated/cooled to supply D-D/D-T fusion for the purpose of neutron generation. Enhancing the pyroelectric neutron generators (PNG) yield is one of the main goals pursued by most of the previously developed techniques/models. Here, the maximum possible neutron yield of a PNG is calculated in which a widely-used pyroelectric crystal (i.e., LiTaO3 with a diameter of 3 cm and height of 1 cm) is applied. This calculation is performed by a simulation procedure including: (1) computation of the PNG potential/current for neutron generation based on new modifications (2) simulation of the deuterium ions acceleration into the target during a thermal cycle (3) simulation of the D-D fusion interaction using the Geant4 toolkit. The results show that the maximum yield of the PNG in the ideal conditions is about 6.4× 106 neutrons per cycle. This study provides a useful approach for determining the upper limit of the expected efficiency for typical PNGs and other compact neutron generators.