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We introduce GRANIITTI, a new Monte Carlo event generator designed especially to solve the enigma of glueballs at the LHC. We discuss the available physics processes, compare the simulations against STAR data from RHIC and span ambitious…

High Energy Physics - Phenomenology · Physics 2023-04-13 Mikael Mieskolainen

We describe the physics and computational power of GRANIITTI Monte Carlo event generator, a new fully multithreaded engine designed for high energy diffraction, written in modern C++. The emphasis is especially on the low-mass domain of…

High Energy Physics - Phenomenology · Physics 2019-10-23 Mikael Mieskolainen

We use a Monte Carlo implementation of recently developped models of exclusive diffractive W, top, Higgs and stop productions to assess the sensitivity of the LHC experiments.

High Energy Physics - Phenomenology · Physics 2015-06-25 C. Royon

A high-accuracy solution of the diffraction problem has become necessary for the treatment of certain special questions of statistical physics. This article reports the creation of a computer program that serves as an instrumental method of…

Optics · Physics 2013-08-30 Vladimir V. Savukov , Igor V. Golubenko

We use a Monte Carlo implementation of recently developped models of exclusive diffractive $W$, top, Higgs and stop productions to assess the sensitivity of the LHC experiments.

High Energy Physics - Phenomenology · Physics 2007-05-23 C. Royon

We consider diffractive processes which can be measured at the LHC. Analysis of diffractive events will give unique information about the high energy asymptotics of hadron scattering. In semihard diffraction one may study the partonic…

High Energy Physics - Phenomenology · Physics 2017-08-23 M. G. Ryskin , A. D. Martin , V. A. Khoze

Sequential Monte Carlo (SMC), or particle filtering, is widely used in nonlinear state-space systems, but its performance often suffers from poorly approximated proposal and state-transition distributions. This work introduces a…

Machine Learning · Computer Science 2026-05-14 Wessel L. van Nierop , Nir Shlezinger , Ruud J. G. van Sloun

We describe an efficient Monte Carlo algorithm for a restricted class of scattering problems in radiation transfer. This class includes many astrophysically interesting problems, including the scattering of ultraviolet and visible light by…

Astrophysics · Physics 2007-05-23 Alan M. Watson , William J. Henney

A boundary-based net-exchange Monte Carlo method was introduced in [1] that allows to bypass the difficulties encountered by standard Monte Carlo algorithms in the limit of optically thick absorption (and/or for quasi-isothermal…

Computational Physics · Physics 2019-03-06 V. Eymet , R. Fournier , S. Blanco , J. L. Dufresne

This paper proposes a new theory and methodology to tackle the problem of unifying distributed analyses and inferences on shared parameters from multiple sources, into a single coherent inference. This surprisingly challenging problem…

Methodology · Statistics 2019-07-22 Hongsheng Dai , Murray Pollock , Gareth Roberts

Monte Carlo evaluation is used to calculate heavy-ion elastic scattering including the center-of-mass correction and the Coulomb interaction.Angular distributions are presented for a number of nuclear pairs over a wide energy range using…

Nuclear Theory · Physics 2015-06-04 W. R. Gibbs , Jean-Pierre Dedonder

We review the basic outline of the highly successful diffusion Monte Carlo technique commonly used in contexts ranging from electronic structure calculations to rare event simulation and data assimilation, and propose a new class of…

Numerical Analysis · Mathematics 2017-10-10 Lek-Heng Lim , Jonathan Weare

A major challenge facing existing sequential Monte-Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results…

Quantum Physics · Physics 2017-09-13 Christopher Granade , Nathan Wiebe

The total cross-section of the $\gamma \gamma \to 4 $ leptons process is known to have a large constant value at high energy, but a complete and exact calculation of related differential spectra does not exist yet. However a complete study…

High Energy Physics - Phenomenology · Physics 2009-10-31 C. Carimalo , W. da Silva , F. Kapusta

The classical Langevin Monte Carlo method looks for samples from a target distribution by descending the samples along the gradient of the target distribution. The method enjoys a fast convergence rate. However, the numerical cost is…

Machine Learning · Statistics 2025-03-07 Zhiyan Ding , Qin Li

A Monte Carlo program based on a three dimensional vector approach was developed to model multiple refractive scattering of X-ray photons in objects with a fine structure. A particular interest was paid to the investigation of lung tissue.…

Medical Physics · Physics 2010-02-02 Anastasiya Khromova

In this article we consider a Monte Carlo-based method to filter partially observed diffusions observed at regular and discrete times. Given access only to Euler discretizations of the diffusion process, we present a new procedure which can…

Numerical Analysis · Mathematics 2020-02-12 Ajay Jasra , Kody Law , Fangyuan Yu

We use a Monte Carlo implementation of recently developped models of double diffractive Higgs production to assess the sensitivity of the LHC experiments.

High Energy Physics - Phenomenology · Physics 2017-08-23 C. Royon

We present powerful new analysis techniques to constrain effective field theories at the LHC. By leveraging the structure of particle physics processes, we extract extra information from Monte-Carlo simulations, which can be used to train…

High Energy Physics - Phenomenology · Physics 2018-09-19 Johann Brehmer , Kyle Cranmer , Gilles Louppe , Juan Pavez

In recent years, a better understanding of the Monte Carlo method has provided us with many new techniques in different areas of statistical physics. Of particular interest are so called cluster methods, which exploit the considerable…

Statistical Mechanics · Physics 2007-05-23 Werner Krauth
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