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Olivares Herrador, J., Latina, A., Aksoy, A., Fuster Martinez, N., Gimeno, B., & Esperante, D. (2024). Implementation of the beam-loading effect in the tracking code RF-track based on a power-diffusive model. Front. Physics, 12, 1348042–11pp.
Abstract: The need to achieve high energies in particle accelerators has led to the development of new accelerator technologies, resulting in higher beam intensities and more compact devices with stronger accelerating fields. In such scenarios, beam-loading effects occur, and intensity-dependent gradient reduction affects the accelerated beam as a consequence of its interaction with the surrounding cavity. In this study, a power-diffusive partial differential equation is derived to account for this effect. Its numerical resolution has been implemented in the tracking code RF-Track, allowing the simulation of apparatuses where transient beam loading plays an important role. Finally, measurements of this effect have been carried out in the CERN Linear Electron Accelerator for Research (CLEAR) facility at CERN, finding good agreement with the RF-Track simulations.
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Gimenez-Alventosa, V., Gimenez, V., & Oliver, S. (2021). PenRed: An extensible and parallel Monte-Carlo framework for radiation transport based on PENELOPE. Comput. Phys. Commun., 267, 108065–12pp.
Abstract: Monte Carlo methods provide detailed and accurate results for radiation transport simulations. Unfortunately, the high computational cost of these methods limits its usage in real-time applications. Moreover, existing computer codes do not provide a methodology for adapting these kinds of simulations to specific problems without advanced knowledge of the corresponding code system, and this restricts their applicability. To help solve these current limitations, we present PenRed, a general-purpose, standalone, extensible and modular framework code based on PENELOPE for parallel Monte Carlo simulations of electron-photon transport through matter. It has been implemented in C++ programming language and takes advantage of modern object-oriented technologies. In addition, PenRed offers the capability to read and process DICOM images as well as to construct and simulate image-based voxelized geometries, so as to facilitate its usage in medical applications. Our framework has been successfully verified against the original PENELOPE Fortran code. Furthermore, the implemented parallelism has been tested showing a significant improvement in the simulation time without any loss in precision of results. Program summary Program title: PenRed: Parallel Engine for Radiation Energy Deposition. CPC Library link to program files: https://doi .org /10 .17632/rkw6tvtngy.1 Licensing provision: GNU Affero General Public License (AGPL). Programming language: C++ standard 2011. Nature of problem: Monte Carlo simulations usually require a huge amount of computation time to achieve low statistical uncertainties. In addition, many applications necessitate particular characteristics or the extraction of specific quantities from the simulation. However, most available Monte Carlo codes do not provide an efficient parallel and truly modular structure which allows users to easily customise their code to suit their needs without an in-depth knowledge of the code system. Solution method: PenRed is a fully parallel, modular and customizable framework for Monte Carlo simulations of the passage of radiation through matter. It is based on the PENELOPE [1] code system, from which inherits its unique physics models and tracking algorithms for charged particles. PenRed has been coded in C++ following an object-oriented programming paradigm restricted to the C++11 standard. Our engine implements parallelism via a double approach: on the one hand, by using standard C++ threads for shared memory, improving the access and usage of the memory, and, on the other hand, via the MPI standard for distributed memory infrastructures. Notice that both kinds of parallelism can be combined together in the same simulation. Moreover, both threads and MPI processes, can be balanced using the builtin load balance system (RUPER-LB [30]) to maximise the performance on heterogeneous infrastructures. In addition, PenRed provides a modular structure with methods designed to easily extend its functionality. Thus, users can create their own independent modules to adapt our engine to their needs without changing the original modules. Furthermore, user extensions will take advantage of the builtin parallelism without any extra effort or knowledge of parallel programming. Additional comments including restrictions and unusual features: PenRed has been compiled in linux systems withg++ of GCC versions 4.8.5, 7.3.1, 8.3.1 and 9; clang version 3.4.2 and intel C++ compiler (icc) version 19.0.5.281. Since it is a C++11-standard compliant code, PenRed should be able to compile with any compiler with C++11 support. In addition, if the code is compiled without MPI support, it does not require any non standard library. To enable MPI capabilities, the user needs to install whatever available MPI implementation, such as openMPI [24] or mpich [25], which can be found in the repositories of any linux distribution. Finally, to provide DICOM processing support, PenRed can be optionally compiled using the dicom toolkit (dcmtk) [32] library. Thus, PenRed has only two optional dependencies, an MPI implementation and the dcmtk library.
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Figueroa, D. G., Florio, A., Torrenti, F., & Valkenburg, W. (2023). CosmoLattice: A modern code for lattice simulations of scalar and gauge field dynamics in an expanding universe. Comput. Phys. Commun., 283, 108586–13pp.
Abstract: This paper describes CosmoGattice, a modern package for lattice simulations of the dynamics of interacting scalar and gauge fields in an expanding universe. CosmoGattice incorporates a series of features that makes it very versatile and powerful: i) it is written in C++ fully exploiting the object oriented programming paradigm, with a modular structure and a clear separation between the physics and the technical details, ii) it is MPI-based and uses a discrete Fourier transform parallelized in multiple spatial dimensions, which makes it specially appropriate for probing scenarios with well -separated scales, running very high resolution simulations, or simply very long ones, iii) it introduces its own symbolic language, defining field variables and operations over them, so that one can introduce differential equations and operators in a manner as close as possible to the continuum, iv) it includes a library of numerical algorithms, ranging from O(delta t(2)) to O(delta t(10)) methods, suitable for simulating global and gauge theories in an expanding grid, including the case of 'self-consistent' expansion sourced by the fields themselves. Relevant observables are provided for each algorithm (e.g. energy densities, field spectra, lattice snapshots) and we note that, remarkably, all our algorithms for gauge theories (Abelian or non-Abelian) always respect the Gauss constraint to machine precision. Program summary Program Title:: CosmoGattice CPC Library link to program files: https://doi .org /10 .17632 /44vr5xssc6 .1 Developer's repository link: http://github .com /cosmolattice /cosmolattice Licensing provisions: MIT Programming language: C++, MPI Nature of problem: The phenomenology of high energy physics in the early universe is typically characterized by non-linear dynamics, which cannot be captured accurately with analytical techniques. In order to fully understand the non-linearities developed in a given scenario, one needs to carry out lattice simulations. A number of public packages for lattice simulations have appeared over the years, but most of them are only capable of simulating scalar fields. However, realistic models of particle physics do contain other kind of field species, such as (Abelian or non-Abelian) gauge fields, whose non-linear dynamics can also play a relevant role in the early universe. Tensor modes representing gravitational waves are also naturally expected in many scenarios. Solution method: CosmoGattice represents a modern code for lattice simulations of scalar-gauge field theories in an expanding universe. It allows for the simulation of the evolution of interacting (singlet) scalar fields, charged scalar fields under U(1) and/or SU(2) gauge groups, and the corresponding associated Abelian and/or non-Abelian gauge fields. From version 1.1 onward, CosmoGattice also allows to simulate the production of gravitational waves. Simulations can be done either in a flat space-time background, or in a homogeneous and isotropic (spatially flat) expanding FLRW background. CosmoGattice provides symplectic integrators, with accuracy ranging from O (delta t(2)) up to O(delta t(10)), to simuate the non-linear dynamics of the appropriate fields in comoving three-dimensional lattices. The code is parallelized with MPI, and uses a discrete Fourier Transform parallelized in multiple spatial dimensions, which makes it a very powerful code for probing physical problems with well-separated scales. Moreover, the code has been designed as a `platform' to implement any system of dynamical equations suitable for discretization on a lattice.
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Oliver, S., Rodriguez Bosca, S., & Gimenez-Alventosa, V. (2024). Enabling particle transport on CAD-based geometries for radiation simulations with penRed. Comput. Phys. Commun., 298, 109091–11pp.
Abstract: Geometry construction is a fundamental aspect of any radiation transport simulation, regardless of the Monte Carlo code being used. Typically, this process is tedious, time-consuming, and error-prone. The conventional approach involves defining geometries using mathematical objects or surfaces. However, this method comes with several limitations, especially when dealing with complex models, particularly those with organic shapes. Furthermore, since each code employs its own format and methodology for defining geometries, sharing and reproducing simulations among researchers becomes a challenging task. Consequently, many codes have implemented support for simulating over geometries constructed via Computer-Aided Design (CAD) tools. Unfortunately, this feature is lacking in penRed and other PENELOPE physics-based codes. Therefore, the objective of this work is to implement such support within the penRed framework. New version program summary Program Title: Parallel Engine for Radiation Energy Deposition (penRed) CPC Library link to program files: https://doi.org/10.17632/rkw6tvtngy.2 Developer's repository link: https://github.com/PenRed/PenRed Code Ocean capsule: https://codeocean.com/capsule/1041417/tree Licensing provisions: GNU Affero General Public License v3 Programming language: C++ standard 2011. Journal reference of previous version: V. Gimenez-Alventosa, V. Gimenez Gomez, S. Oliver, PenRed: An extensible and parallel Monte-Carlo framework for radiation transport based on PENELOPE, Computer Physics Communications 267 (2021) 108065. doi:https://doi.org/10.1016/j.cpc.2021.108065. Does the new version supersede the previous version?: Yes Reasons for the new version: Implements the capability to simulate on CAD constructed geometries, among many other features and fixes. Summary of revisions: All changes applied through the code versions are summarized in the file CHANGELOG.md in the repository package. Nature of problem: While Monte Carlo codes have proven valuable in simulating complex radiation scenarios, they rely heavily on accurate geometrical representations. In the same way as many other Monte Carlo codes, penRed employs simple geometric quadric surfaces like planes, spheres and cylinders to define geometries. However, since these geometric models offer a certain level of flexibility, these representations have limitations when it comes to simulating highly intricate and irregular shapes. Anatomic structures, for example, require detailed representations of organs, tissues and bones, which are difficult to achieve using basic geometric objects. Similarly, complex devices or intricate mechanical systems may have designs that cannot be accurately represented within the constraints of such geometric models. Moreover, when the complexity of the model increases, geometry construction process becomes more difficult, tedious, time-consuming and error-prone [2]. Also, as each Monte Carlo geometry library uses its own format and construction method, reproducing the same geometry among different codes is a challenging task. Solution method: To face the problems stated above, the objective of this work is to implement the capability to simulate using irregular and adaptable meshed geometries in the penRed framework. This kind of meshes can be constructed using Computer-Aided Design (CAD) tools, the use of which is very widespread and streamline the design process. This feature has been implemented in a new geometry module named “MESH_BODY” specific for this kind of geometries. This one is freely available and usable within the official penRed package1. It can be used since penRed version 1.9.3b and above.
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Villaescusa-Navarro, F. et al, & Villanueva-Domingo, P. (2023). The CAMELS Project: Public Data Release. Astrophys. J. Suppl. Ser., 265(2), 54–14pp.
Abstract: The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lya spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at .
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