Related papers: LCG MCDB -- a Knowledgebase of Monte Carlo Simulat…
First of all, this paper presents some improvements of DSMC method in the form of new schemes and approaches, that, for a wide class of problems, increase performance and reduce the demands on computer resources. The most important…
We compare Monte Carlo event generators dedicated to simulating the production and decay of extra-dimensional black holes at the Large Hadron Collider.
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…
Simulation-guided design represents a fundamental contribution towards the development of modern semiconductor devices aiming to reach high-performance particle detection, identification and tracking, and constitutes a strategic element of…
A Monte Carlo simulator is presented to reproduce data of nucleus-nucleus interactions at high energies. The program is designed in a microscopic point of view, where the cascade approach is applied. Moreover, each nucleon from both the…
Stochastic gradient Markov chain Monte Carlo (SG-MCMC) has become increasingly popular for simulating posterior samples in large-scale Bayesian modeling. However, existing SG-MCMC schemes are not tailored to any specific probabilistic…
Computer power is a constantly increasing demand in scientific data analyses, in particular when Markov Chain Monte Carlo (MCMC) methods are involved, for example for estimating integral functions or Bayesian posterior probabilities. In…
Monte Carlo methods are widely used to estimate observables in many-body quantum systems. However, conventional sampling schemes often require a large number of samples to achieve sufficient accuracy. In this work we propose the…
Multicanonical MCMC (Multicanonical Markov Chain Monte Carlo; Multicanonical Monte Carlo) is discussed as a method of rare event sampling. Starting from a review of the generic framework of importance sampling, multicanonical MCMC is…
Markov-chain Monte Carlo sampling has become a standard technique for exploring the posterior distribution of cosmological parameters constrained by observations of CMB anisotropies. Given an infinite amount of time, any MCMC sampler will…
Markov chain Monte Carlo (MCMC) algorithms are indispensable when sampling from a complex, high-dimensional distribution by a conventional method is intractable. Even though MCMC is a powerful tool, it is also hard to control and tune in…
An increasing number of applications are exploiting sampling-based algorithms for planning, optimization, and inference. The Markov Chain Monte Carlo (MCMC) algorithms form the computational backbone of this emerging branch of machine…
Advancements in scientific instrument sensors and connected devices provide unprecedented insight into ongoing experiments and present new opportunities for control, optimization, and steering. However, the diversity of sensors and…
Monte Carlo generation of high energy particle collisions is a critical tool for both theoretical and experimental particle physics, connecting perturbative calculations to phenomenological models, and theory predictions to full detector…
CASCADE is a full hadron level Monte Carlo event generator for e-p, gamma-p and p-p_bar processes, which uses the CCFM evolution equation for the initial state cascade in a backward evolution approach supplemented with off-shell matrix…
Multilevel Monte Carlo (MLMC) is a recently proposed variation of Monte Carlo (MC) simulation that achieves variance reduction by simulating the governing equations on a series of spatial (or temporal) grids with increasing resolution.…
A large scale Monte Carlo production has been pursued since spring 2018 for the ILD detector optimization studies based on physics benchmark processes. A production system based on ILCDirac has been developed to produce samples in timely…
The Monte Carlo for lepton pair production and tau decays consist of KKMC for lepton pair production, tauola for tau lepton decays and photos for radiative corrections in decays. An effort for adaptation of the system for precision data to…
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.…
We present the Local Self-Balancing sampler (LSB), a local Markov Chain Monte Carlo (MCMC) method for sampling in purely discrete domains, which is able to autonomously adapt to the target distribution and to reduce the number of target…