Related papers: Physics Data Management Tools for Monte Carlo Tran…
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…
Recent efforts for the improvement of the accuracy of physics data libraries used in particle transport are summarized. Results are reported about a large scale validation analysis of atomic parameters used by major Monte Carlo systems…
The role of data libraries as a collaborative tool across Monte Carlo codes is discussed. Some new contributions in this domain are presented; they concern a data library of proton and alpha ionization cross sections, the development in…
Simulating physical systems is a core component of scientific computing, encompassing a wide range of physical domains and applications. Recently, there has been a surge in data-driven methods to complement traditional numerical simulations…
The application of quantum computing to data management has attracted growing interest, yet remains constrained by a limited understanding of how the physical behaviour of quantum devices relates to the structure and difficulty of database…
This extended abstract briefly summarizes ongoing research activity on the evaluation and experimental validation of physics methods for photon and electron transport. The analysis includes physics models currently implemented in Geant4 as…
In a landscape where scientific discovery is increasingly driven by data, the integration of machine learning (ML) with traditional scientific methodologies has emerged as a transformative approach. This paper introduces a novel,…
An investigation is in progress to evaluate extensively and quantitatively the possible benefits and drawbacks of new programming paradigms in a Monte Carlo simulation environment, namely in the domain of physics modeling. The prototype…
As simulation system, the variety of physics processes implemented is one of the most important functionalities. In that sense, Geant4 is one of the most powerful simulation toolkits. Its flexibility and expansibility brought by…
During the last decade we have witnessed an impressive development in so-called interpreted languages and computational environments such as Maple, Mathematica, IDL, Matlab etc. Problems which until recently were typically solved on…
Monte Carlo particle transport codes are well established on classical hardware and are considered as the reference tool for nuclear applications. In a growing number of domains, the design of algorithms is progressively shifting towards…
We report an investigation of data analysis methods derived from other disciplines, which we applied to physics software systems. They concern the analysis of inequality, trend analysis and the analysis of diversity. The analysis of…
The ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. These systems are described in detail, including software infrastructure and workflows, distributed data and workload management,…
In this paper, we present the High Energy Physics data format, processing toolset and analysis library a4, providing fast I/O of structured data using the Google protocol buffer library. The overall goal of a4 is to provide physicists with…
Exponential increases in scientific experimental data are outstripping the rate of progress in silicon technology. As a result, heterogeneous combinations of architectures and process or device technologies are increasingly important to…
We present mechanoChemML, a machine learning software library for computational materials physics. mechanoChemML is designed to function as an interface between platforms that are widely used for machine learning on one hand, and others for…
Understanding the physical world is a continuous process of trial and error. It requires theoretical background and tools to find out the theory's accuracy. Particles motion through matter, and their energy loss is one such process. Testing…
The set of externally visible properties associated with process variables in the Experimental Physics and Industrial Control System (EPICS) is predefined in the EPICS base distribution and is therefore not extensible by plug-compatible…
The use of machine learning algorithms to predict behaviors of complex systems is booming. However, the key to an effective use of machine learning tools in multi-physics problems, including combustion, is to couple them to physical and…
Modern analysis of high energy physics (HEP) data needs advanced statistical tools to separate signal from background. A C++ package has been implemented to provide such tools for the HEP community. The package includes linear and quadratic…