Related papers: HepSim: a repository with predictions for high-ene…
We review the main software and computing challenges for the Monte Carlo physics event generators used by the LHC experiments, in view of the High-Luminosity LHC (HL-LHC) physics programme. This paper has been prepared by the HEP Software…
Monte Carlo simulations are based on the manipulation of random numbers to evaluate probable outcomes, with applicability in a variety of different fields. By assigning probabilities, which can be determined a priori, to various events, it…
This program can be used to simulate polarised nucleon - nucleon collisions at high energies. Spins of colliding particles are taken into account. The program allows to calculate cross sections for various processes.
The hybrid Monte Carlo (HMC) algorithm is arguably the most efficient sampling method for general probability distributions of continuous variables. Together with exact Fourier acceleration (EFA) the HMC becomes equivalent to direct…
A new data format for Monte Carlo (MC) events, or any structural data, including experimental data, is discussed. The format is designed to store data in a compact binary form using variable-size integer encoding as implemented in the…
We propose a data format for Monte Carlo (MC) events, or any structural data, including experimental data, in a compact binary form using variable-size integer encoding as implemented in the Google's Protocol Buffers package. This approach…
A new Monte Carlo program for photohadronic interactions of relativistic nucleons with an ambient photon radiation field is presented. The event generator is designed to fulfil typical astrophysical requirements, but can also be used for…
A multi-platform validation and analysis framework for public Monte Carlo simulation for high-energy particle collisions is discussed. The front-end of this framework uses the Python programming language, while the back-end is written in…
The installation and maintenance of scientific software for research in experimental, phenomenological, and theoretical High Energy Physics (HEP) requires a considerable amount of time and expertise. While many tools are available to make…
Sampling-based inference has seen a surge of interest in recent years. Hamiltonian Monte Carlo (HMC) has emerged as a powerful algorithm that leverages concepts from Hamiltonian dynamics to efficiently explore complex target distributions.…
The comparison of experimental data and theoretical predictions is important for our understanding of the mechanisms for interactions and particle production in hadron collisions, both at the Large Hadron Collider and at the Relativistic…
A simple Monte Carlo (MC) algorithm for the simulation of the passage of low-energy gamma rays and electrons through any material medium is presented. The algorithm includes several approximations that accelerate the simulation while…
This is a report from the Libraries and Tools Working Group of the High Energy Physics Forum for Computational Excellence. It presents the vision of the working group for how the HEP software community may organize and be supported in order…
The Hybrid Monte Carlo (HMC) algorithm currently is the favorite scheme to simulate quantum chromodynamics including dynamical fermions. In this talk-which is intended for a non-expert audience--I want to bring together methodical and…
Goupil is a software library designed for the Monte Carlo transport of low-energy gamma-rays, such as those emitted from radioactive isotopes. The library is distributed as a Python module. It implements a dedicated backward sampling…
We present an elementary and self-contained account of the analogies existing between classical diffusion and the imaginary-time evolution of quantum systems. These analogies are used to develop a new quantum simulation method which allows…
RefDB is the CMS Monte Carlo Reference Database. It is used for recording and managing all details of physics simulation, reconstruction and analysis requests, for coordinating task assignments to world-wide distributed Regional Centers,…
We propose a hybrid Monte Carlo (HMC) technique applicable to high-dimensional multivariate normal distributions that effectively samples along chaotic trajectories. The method is predicated on the freedom of choice of the HMC momentum…
Hamiltonian Monte Carlo (HMC) samples efficiently from high-dimensional posterior distributions with proposed parameter draws obtained by iterating on a discretized version of the Hamiltonian dynamics. The iterations make HMC…
Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and…