Related papers: Re-engineering a nanodosimetry Monte Carlo code in…
A GEANT4-based simulation is developed for the endcap time of flight (ETOF) upgrade based on multi-gap resistive plate chambers (MRPC) for the BESIII experiment. The MRPC prototype and the simulation method are described. Using a full…
The GENFIT toolkit, initially developed at the Technische Universitaet Muenchen, has been extended and modified to be more general and user-friendly. The new GENFIT, called GENFIT2, provides track representation, track-fitting algorithms…
Purpose: This work introduces a new lattice geometry library, egs_lattice, into the EGSnrc Monte Carlo code, which can be used for both modeling very large (previously unfeasible) quantities of geometries and establishing recursive boundary…
During the past years several variance reduction techniques for Monte Carlo electron transport have been developed in order to reduce the electron computation time transport for absorbed dose distribution. We have implemented the Macro…
The new generation of astroparticle experiments will use technologies common to High Energy Physics. Among such technologies a central place is given to the role of simulation.
Modern particle physics experiments face an increasing demand for high-fidelity detector simulation as luminosities rise and computational requirements approach the limits of available resources. Deep generative models have emerged as…
There has been a lot of research interest in modified gravity theories which utilise the Vainshtein mechanism to recover standard general relativity in regions with high matter density, such as the Dvali-Gabadadze-Porrati and Galileon…
Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental…
We discuss some examples where numerical simulations based on effectively fabricated nanostructures can provide additional insights into an experiment. Focusing on plasmonics, we study Fano resonant systems for optical trapping, realistic…
Histogram-based template fits are the main technique used for estimating parameters of high energy physics Monte Carlo generators. Parametrized neural network reweighting can be used to extend this fitting procedure to many dimensions and…
A nanoscopic simulation for an acceleration sensor is aimed based on the piezoresistive effect of carbon nanotubes (CNTs). Therefore, a compact model is built from density functional theory (DFT), compared with results of molecular dynamics…
Purpose: To develop a Monte Carlo (MC) therapeutic dose calculation toolkit of a recently released ring gantry linac in Geant4 (Version 10.7) for secondary dose validation of radiotherapy plan. Methods: For the Halcyon (Varian Medical…
Neutron penumbral imaging technique has been successfully used as the diagnosis method in Inertial Confined Fusion. To help the design of the imaging systems in the future in CHINA. We construct the Monte carlo imaging system by Geant4. Use…
A linear Breit-Wheeler module for the code Geant4 has been developed. This allows signal-to-noise ratio calculations of linear Breit-Wheeler detection experiments to be performed within a single framework. The interaction between two photon…
BoGEMMS, (Bologna Geant4 Multi-Mission Simulator) is a software project for fast simulation of payload on board of scientific satellites for prompt background evaluation that has been developed at the INAF/IASF Bologna. By exploiting the…
We present {\gamma} spectroscopy validation measurements for the Geant4 radioactive decay simulation for a selected range of isotopes using a simple experimental setup. Using these results we point out problems in the decay simulation and…
A new release of the parametric detector Monte Carlo program \verb+SIMDET+ (version 4.01) is now available. We describe the principles of operation and the usage of this program to simulate the response of a detector for the TESLA linear…
Diffractive optical neural networks (DONNs) have attracted lots of attention as they bring significant advantages in terms of power efficiency, parallelism, and computational speed compared with conventional deep neural networks (DNNs),…
Gaussian process regression techniques have been used in fluid mechanics for the reconstruction of flow fields from a reduction-of-dimension perspective. A main ingredient in this setting is the construction of adapted covariance functions,…
The focus in this paper is an analysis of existing state of the arts directed toward the development of the next generation of vibration damping systems. The research work concentrates on an investigation related to…