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Numerous challenges persist in High Energy Physics (HEP), the addressing of which requires advancements in detection technology, computational methods, data analysis frameworks, and phenomenological designs. We provide a concise yet…
The engineering design of a particle detector is usually performed in a Computer Aided Design (CAD) program, and simulation of the detector's performance can be done with a Geant4-based program. However, transferring the detector design…
The production, application, and/or measurement of polarised X-/gamma rays are key to the fields of synchrotron science and X-/gamma-ray astronomy. The design, development and optimisation of experimental equipment utilised in these fields…
The development of a package for the management of physics data is described: its design, implementation and computational benchmarks. This package improves the data management tools originally developed for Geant4 physics models based on…
This study investigates the application of large language models, specifically GPT-4, to enhance programming education. The research outlines the design of a web application that uses GPT-4 to provide feedback on programming tasks, without…
This paper summarizes Geant4 contribution to scientific research over the past 25 years through a scientometric analysis of the results with which it has been associated. The scientometric data collected from scholarly literature and…
Geant4 Detector Construction Pattern (GDCP) is a C++ package containing a set of utility classes for developers to utilize during the detector construction phase of a Geant4 application. The main objective of this study is to provide an…
Quantum computing offers a new paradigm for advancing high-energy physics research by enabling novel methods for representing and reasoning about fundamental quantum mechanical phenomena. Realizing these ideals will require the development…
Experiments measuring fission observables encounter false coincidences arising from timing overlap of separate fission product decays. Simulations of both fission observables and particles in detector systems exist, but have not yet been…
A macroscopic reconstruction is developed to infer iRPC performance using Geant4 observables and one experimental anchor. The Geant4 energy deposition is used to estimate the primary ionization yield, while the efficiency turn-on is modeled…
The proposed work demonstrates the results of creating and investigating the mathematical model of the source of fast neutrons. The model carrier is a computer program developed in the C++ programming language in the Linux operating system…
Quantum computing, leveraging quantum phenomena like superposition and entanglement, is emerging as a transformative force in computing technology, promising unparalleled computational speed and efficiency crucial for engineering…
We present a novel Python tool for the analysis of Geant4 simulations that enhances our understanding of coherent phenomena occurring during the interaction of charged particles with crystal planes. This tool compares the total energy of…
In recent years, advancements in artificial intelligence (AI) have led to the development of large language models like GPT-4, demonstrating potential applications in various fields, including education. This study investigates the…
The Geant4 toolkit is the leading software for the simulation of particle transport through matter, widely used in nuclear physics, high-energy physics, and medical physics. However, the initial learning curve for new developers can be…
The pace of improvement in the performance of conventional computer hardware has slowed significantly during the past decade, largely as a consequence of reaching the physical limits of manufacturing processes. To offset this slowdown, new…
An accurate description of interactions between thermal neutrons (below 4 eV) and materials is key to simulate the transport of neutrons in a wide range of applications such as criticality-safety, reactor physics, compact accelerator-driven…
There has been a recent explosion in research into machine-learning-based generative modeling to tackle computational challenges for simulations in high energy physics (HEP). In order to use such alternative simulators in practice, we need…
High density electromagnetic sandwich calorimeters with high readout granularity are considered for many future collider and fix-target experiments. Optimization of the calorimeter structure from the point of view of the electromagnetic…
Deep Neural Networks (DNNs) come into the limelight in High Energy Physics (HEP) in order to manipulate the increasing amount of data encountered in the next generation of accelerators. Recently, the HEP community has suggested Generative…