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We introduce a method for non-uniform random number generation based on sampling a physical process in a controlled environment. We demonstrate one proof-of-concept implementation of the method that reduces the error of Monte Carlo…

Other Computer Science · Computer Science 2020-04-24 James Timothy Meech , Phillip Stanley-Marbell

The energy dependence of the electron - positron hadronic cross section can be measured not only by a straightforward energy scan, but also by means of the radiative return method. To provide extensive comparisons between theory and…

High Energy Physics - Phenomenology · Physics 2009-11-07 H. Czyz , J. H. Kuehn , G. Rodrigo

A new version of Monte Carlo generator ELRADGEN for simulation of real photon emission in elastic electron-proton scattering is presented. The extensions in the new version include opportunity to deal with polarized particles:…

High Energy Physics - Phenomenology · Physics 2009-12-14 I. Akushevich , A. Ilyichev , N. Shumeiko

Ultra-peripheral heavy-ion collisions (UPCs) provide a distinct environment for high-energy QCD research, focusing on the production of vector mesons. This proceeding details recent advancements in the Sar$t$re Monte Carlo event generator,…

High Energy Physics - Phenomenology · Physics 2025-11-18 Vaidehi Nattoja , Tobias Toll

A brief introduction to the statistical hadronization approach to particle production in relativistic heavy-ion collisions is given. In the context of fluid dynamics modeling various aspects of hadron emission at the freeze-out are…

Nuclear Theory · Physics 2022-07-13 Radoslaw Ryblewski

We extend the previously developed small $x$ parton shower algorithm to include the kinematic constraint effect and $k_t$ resummation effect. This work enables the Monte Carlo generator to simultaneously resum large $k_t$ and small $x$…

High Energy Physics - Phenomenology · Physics 2023-07-11 Yu Shi , Shu-Yi Wei , Jian Zhou

It is shown that superefficient Monte Carlo computations can be carried out by using chaotic dynamical systems as non-uniform random-number generators. Here superefficiency means that the expectation value of the square of the error…

chao-dyn · Physics 2007-05-23 Ken Umeno

The use of generative models to sample equilibrium distributions of many-body systems, as first demonstrated by Boltzmann Generators, has attracted substantial interest due to their ability to produce unbiased and uncorrelated samples in…

Statistical Mechanics · Physics 2025-10-23 Maximilian Schebek , Frank Noé , Jutta Rogal

We present a Cross-Entropy based population Monte Carlo algorithm. This methods stands apart from previous work in that we are not optimizing a mixture distribution. Instead, we leverage deterministic mixture weights and optimize the…

Computation · Statistics 2022-02-09 Caleb Miller , Jem N. Corcoran , Michael D. Schneider

The connection between analytic and Monte Carlo calculations of soft gluon emission is reanalyzed in light of recent, theoretical developments in resummation. An alternative Monte Carlo algorithm is suggested which incorporates (1)…

High Energy Physics - Phenomenology · Physics 2007-05-23 S. Mrenna

Standard Monte Carlo computation is widely known to exhibit a canonical square-root convergence speed in terms of sample size. Two recent techniques, one based on control variate and one on importance sampling, both derived from an…

Computation · Statistics 2023-03-13 Henry Lam , Haofeng Zhang

Recently the collider physics community has seen significant advances in the formalisms and implementations of event generators. This review is a primer of the methods commonly used for the simulation of high energy physics events at…

The montecarlo method, which is quite commonly used to solve maximum entropy problems in statistical physics, can actually be used to solve inverse problems in a much wider context. The probability distribution which maximizes entropy can…

Statistical Mechanics · Physics 2007-05-23 Jan Naudts

We consider systems of stochastic differential equations with multiple scales and small noise and assume that the coefficients of the equations are ergodic and stationary random fields. Our goal is to construct provably-efficient importance…

Probability · Mathematics 2015-09-29 Konstantinos Spiliopoulos

We present the Monte Carlo generator tuning strategy followed, and the tools developed, by the MCnet CEDAR project. We also present new tuning results for the Pythia 6.4 event generator which are based on event shape and hadronisation…

High Energy Physics - Phenomenology · Physics 2009-06-02 Andy Buckley , Hendrik Hoeth , Heiko Lacker , Holger Schulz , Eike von Seggern

In this paper, we propose a discontinuous Hamilton Monte Carlo (DHMC) to sample from dimensional varying distributions, and particularly the grand canonical ensemble. The DHMC was proposed in [Biometrika, 107(2)] for discontinuous potential…

Numerical Analysis · Mathematics 2025-05-16 Lei Li , Xiangxian Luo , Yinchen Luo

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

The Monte Carlo for lepton pair production andtau 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…

High Energy Physics - Phenomenology · Physics 2021-12-15 Sw. Banerjee , D. Biswas , T. Przedzinski , Z. Was

A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm is shown to thermalize well below the Mode Coupling temperature and to outperform other…

Statistical Mechanics · Physics 2009-05-21 L. A. Fernandez , V. Martin-Mayor , P. Verrocchio

Computing systems interacting with real-world processes must safely and reliably process uncertain data. The Monte Carlo method is a popular approach for computing with such uncertain values. This article introduces a framework for…

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