Related papers: Next generation input-output data format for HEP u…
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…
In high-energy physics, Monte Carlo event generators (MCEGs) are used to simulate the interactions of high energy particles. MCEG event records store the information on the simulated particles and their relationships, and thus reflects the…
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…
ProIO is a new event-oriented streaming data format which utilizes Google's Protocol Buffers (protobuf) to be flexible and highly language-neutral. The ProIO concept is described here along with its software implementations. The performance…
A file repository for calculations of cross sections and kinematic distributions using Monte Carlo generators for high-energy collisions is discussed. The repository is used to facilitate effective preservation and archiving of data from…
In this paper we describe a HepML format and a corresponding C++ library developed for keeping complete description of parton level events in a unified and flexible form. HepML tags contain enough information to understand what kind of…
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…
We introduce a variant of the Hybrid Monte Carlo (HMC) algorithm to address large-deviation statistics in stochastic hydrodynamics. Based on the path-integral approach to stochastic (partial) differential equations, our HMC algorithm…
Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be…
HEP-Frame is a new C++ package designed to efficiently perform analyses of data sets from a very large number of events, like those available at the Large Hadron Collider (LHC) at CERN, Geneva. It mainly targets high performance servers and…
We present a scalable Bayesian framework for the analysis of confocal fluorescence spectroscopy data, addressing key limitations in traditional fluorescence correlation spectroscopy methods. Our framework captures molecular motion,…
Monte Carlo / Dynamic Code (MC/DC) is a portable Monte Carlo neutron transport package for rapid numerical methods exploration in heterogeneous and HPC contexts, developed under the auspices of the Center for Exascale Monte Carlo Neutron…
We design and implement HPMC, a scalable hard particle Monte Carlo simulation toolkit, and release it open source as part of HOOMD-blue. HPMC runs in parallel on many CPUs and many GPUs using domain decomposition. We employ BVH trees…
Monte Carlo simulations play a crucial role in all stages of particle collider experiments. There has been a long-term trend in HEP of both increasing collision energies and the luminosity. As a result, the requirements for MC simulations…
In this article, we present the High-Performance Output (HiPO) data format developed at Jefferson Laboratory for storing and analyzing data from Nuclear Physics experiments. The format was designed to efficiently store large amounts of…
Carlo is a Monte Carlo simulation framework written in Julia. It provides MPI-parallel scheduling, organized storage of input, checkpoint, and output files, as well as statistical postprocessing. With a minimalist design, it aims to aid the…
The AcerMC Monte Carlo generator is dedicated to the generation of Standard Model background processes which were recognised as critical for the searches at LHC, and generation of which was either unavailable or not straightforward so far.…
A general purpose, self-adapting, Monte Carlo (MC) event generator (simulator) is described. The high efficiency of the MC, that is small maximum weight or variance of the MC weight is achieved by means of dividing the integration domain…
Hybrid Monte Carlo (HMC) generates samples from a prescribed probability distribution in a configuration space by simulating Hamiltonian dynamics, followed by the Metropolis (-Hastings) acceptance/rejection step. Compressible HMC (CHMC)…
We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing…