Related papers: HepSim: a repository with predictions for high-ene…
Since the {\tt KKMC} program was published for the first time over 20 years ago, it has gained popularity and was exploited in a broad spectrum of applications. The core part of the program itself did not change much. In contrast, some of…
Hamiltonian Monte Carlo (HMC) is a Markov chain algorithm for sampling from a high-dimensional distribution with density $e^{-f(x)}$, given access to the gradient of $f$. A particular case of interest is that of a $d$-dimensional Gaussian…
Setting up the infrastructure to manage a software project can become a task as significant writing the software itself. A variety of useful open source tools are available, such as Web-based viewers for version control systems, "wikis" for…
Accurate particle simulations are essential for the next generation of experiments in astroparticle physics. The Monte Carlo simulation library PROPOSAL is a flexible tool to efficiently propagate high-energy leptons and photons through…
We propose to develop a high-energy heavy-ion experimental database and make it accessible to the scientific community through an on-line interace. This database will be searchable and cross-indexed with relevant publications, including…
In this white paper, we describe characteristics of tools for classical simulations of quantum computational devices appropriate for High Energy Physics applications.
A key difficulty that arises from real event data is imprecision in the recording of event time-stamps. In many cases, retaining event times with a high precision is expensive due to the sheer volume of activity. Combined with practical…
Motivated by applications of quantum computers in Gibbs sampling from continuous real-valued functions, we ask whether such algorithms can provide practical advantages for machine learning models trained on classical data and seek measures…
Recently, the Hamilton Monte Carlo (HMC) has become widespread as one of the more reliable approaches to efficient sample generation processes. However, HMC is difficult to sample in a multimodal posterior distribution because the HMC chain…
We present a new Subset Simulation approach using Hamiltonian neural network-based Monte Carlo sampling for reliability analysis. The proposed strategy combines the superior sampling of the Hamiltonian Monte Carlo method with…
A common problem in particle physics is the requirement to reproduce comparisons between data and theory when the theory is a (general purpose) Monte Carlo simulation and the data are measurements of final state observables in high energy…
Monte Carlo simulations are powerful tools for understanding the effects of radiation interactions within detector devices allowing not only to evaluate typical estimates for experimental measurements and to serve as means for designing…
Extension of the open-source simulation package GSEIM for power electronics applications is presented. Recent developments in GSEIM, including those oriented specifically towards power electronic circuits, are described. Some examples of…
We introduce a general Monte Carlo scheme for achieving atomistic simulations with monoelectronic Hamiltonians including the thermalization of both nuclear and electronic degrees of freedom. The kinetic Monte Carlo algorithm is used to…
We present a novel probabilistic programming framework that couples directly to existing large-scale simulators through a cross-platform probabilistic execution protocol, which allows general-purpose inference engines to record and control…
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…
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)…
The current and upcoming generation of Very Large Volume Neutrino Telescopes---collecting unprecedented quantities of neutrino events---can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the…
SUSYGEN is a Monte Carlo program designed for computing distributions and generating events for MSSM sparticle production in e+ e- collisions. The Supersymmetric (SUSY) mass spectrum may either be supplied by the user, or can alternatively…
Monte Carlo simulations are a crucial component when analysing the Standard Model and New physics processes at the Large Hadron Collider. This paper aims to explore the performance of generative models for complementing the statistics of…