Related papers: McMule -- a Monte Carlo generator for low energy p…
Observations of the large-scale structure (LSS) provide a powerful test of gravity on cosmological scales, but high-resolution N-body simulations of modified gravity (MG) are prohibitively expensive. We present MG-NECOLA, a convolutional…
We consider Monte Carlo approximations to the maximum likelihood estimator in models with intractable norming constants. This paper deals with adaptive Monte Carlo algorithms, which adjust control parameters in the course of simulation. We…
Quantum Monte Carlo (QMC) methods deliver highly accurate electronic structure calculations but are computationally intensive. The quantum Monte Carlo kernel library (QMCkl) provides a modular, portable collection of high-performance…
Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also…
A muon collider would be a powerful tool for exploring the energy-frontier with leptons, and would complement the studies now under way at the LHC. Such a device would offer several important benefits. Muons, like electrons, are point…
A WEB-portal HepWeb allows users to perform the most popular calculations in high energy physics - calculations of hadron-hadron, hadron-nucleus and nucleus-nucleus interaction cross sections as well as calculations of secondary particles…
Hadron production in lepton-nucleus interactions at high-energies is considered in framework of developing Monte Carlo event generator HARDPING (HARD Probe INteraction Generator). Such effects as formation length, energy loss and multiple…
The Monte Carlo program \texttt{SUSYGEN}, initially designed for computing distributions and generating events for supersymmetric particle production in $e^+e^-$ collisions, has now been upgraded to study supersymmetric processes at linear…
A diffusion Monte Carlo algorithm is introduced that can determine the correct nodal structure of the wave function of a few-fermion system and its ground-state energy without an uncontrolled bias. This is achieved by confining signed…
Monte Carlo simulations are one of the major tools in statistical physics, complex system science, and other fields, and an increasing number of these simulations is run on distributed systems like clusters or grids. This raises the issue…
A comparison of theoretical results on NNLO leptonic and hadronic corrections to Bhabha scattering with the Monte Carlo generator BabaYaga@NLO used at meson factories is given. Complete NLO virtual corrections to the $e^+e^- \to \mu^+ \mu^-…
We present an extension of the Monte Carlo Event Generator Whizard which includes chargino production at the ILC at NLO. We include photons using both a fixed order and a resummation approach. While the fixed order approach suffers from…
Langevin Monte Carlo (LMC) and its stochastic gradient versions are powerful algorithms for sampling from complex high-dimensional distributions. To sample from a distribution with density $\pi(\theta)\propto \exp(-U(\theta)) $, LMC…
We summarise the motivation for, and the status of, the tools developed by CEDAR/MCnet for validating and tuning Monte Carlo event generators for the LHC against data from previous colliders. We then present selected preliminary results…
Next steps in development of the KrkNLO method of implementing NLO QCD corrections to hard processes in parton shower Monte Carlo programs are presented. This new method is a simpler alternative to other well-known approaches, such as…
We have written the Exclusive Hadronic Monte Carlo Event (ExHuME) generator. ExHuME implements the perturbative QCD calculation of Khoze, Martin and Ryskin of the process pp-> p+X+p, where X is a centrally produced colour singlet system.
Markov chain Monte Carlo (MCMC) methods are a powerful but computationally expensive way of performing non-parametric Bayesian inference. MCMC proposals which utilise gradients, such as Hamiltonian Monte Carlo (HMC), can better explore the…
This paper introduces quasi-Monte Carlo latent variable models (QLVMs): a class of deep generative models that are specialized for finding extremely low-dimensional and interpretable embeddings of high-dimensional datasets. Unlike standard…
Multilevel Monte Carlo (MLMC) reduces the total computational cost of financial option pricing by combining SDE approximations with multiple resolutions. This paper explores a further avenue for reducing cost and improving power efficiency…
We propose a computational strategy for NLO+PS simulations in the MC@NLO framework that starts from Born-accurate (LO) events and reweights them to the full MC@NLO S-event weight, while generating H-events separately. We validate the…