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In this paper, a Monte Carlo based approach for the quantification of the importance of the scattering input parameters with respect to the failure probability is presented. Using the basic idea of the alpha-factors of the First Order…

Computation · Statistics 2024-08-14 Thomas Most

The mechanism for the generation of multipole moments due to an external field is presented for the Born-Infeld charged particle. The 'polarizability coefficient' for arbitrary l-pole moment is calculated. The l-th coefficient is…

High Energy Physics - Theory · Physics 2008-11-26 Dariusz Chruscinski , Jerzy Kijowski

The Monte Carlo method is a thriving and mathematically beautiful numerical technique used extensively, nowadays, to deal with many demanding problems in diverse fields. Here, we present an iterative Monte Carlo algorithm to work out very…

Computational Physics · Physics 2024-08-02 Martín Chávez-Páez , Enrique González-Tovar , Guillermo Iván Guerrero-García

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

This paper considers inference for a function of a parameter vector in a partially identified model with many moment inequalities. This framework allows the number of moment conditions to grow with the sample size, possibly at exponential…

Statistics Theory · Mathematics 2018-07-02 Alexandre Belloni , Federico Bugni , Victor Chernozhukov

Torsional-space Monte Carlo simulations of flexible molecules are usually based on the assumption that all values of dihedral angles have equal probability in the absence of atomic interactions. In the present paper it is shown that this…

Chemical Physics · Physics 2007-05-23 Andreas Kraemer

We apply a diagrammatic Monte Carlo method to the problem of an impurity interacting resonantly with a homogeneous Fermi bath for a quasi-two-dimensional setup. Notwithstanding the series divergence, we can show numerically that the three…

Quantum Gases · Physics 2014-09-18 Peter Kroiss , Lode Pollet

Variational wave functions used in the variational Monte Carlo (VMC) method are extensively improved to overcome the biases coming from the assumed variational form of the wave functions. We construct a highly generalized variational form…

Strongly Correlated Electrons · Physics 2008-10-27 Daisuke Tahara , Masatoshi Imada

We introduce modifications to Monte Carlo simulations of the Feynman path integral that improve sampling of localised interactions. The new algorithms generate trajectories in simple background potentials designed to concentrate them about…

Quantum Physics · Physics 2025-08-06 Ivan Ahumada , James P. Edwards

The work presents the recent developments in Quantum Monte Carlo calculations for nuclear systems including strange degrees of freedom. The Auxiliary Field Diffusion Monte Carlo algorithm has been extended to the strange sector by the…

Nuclear Theory · Physics 2013-11-27 Diego Lonardoni

The subsurface flow is usually subject to uncertain porous media structures. In most cases, however, we only have partial knowledge about the porous media properties. A common approach is to model the uncertain parameters of porous media as…

Numerical Analysis · Mathematics 2019-10-11 Yang Liu , Jingfa Li , Shuyu Sun , Bo Yu

Particle-level measurements, especially of differential cross-sections, made in fiducial regions of phase-space have a high degree of model-independence and can therefore be used to give information about a wide variety of Beyond the…

High Energy Physics - Phenomenology · Physics 2019-10-02 J. M. Butterworth

A method is given for generating a bounded invariant of a differential system with a given set of initial conditions around a point $x_0$. This invariant has the form of a tube centered on the Euler approximate solution starting at $x_0$,…

Systems and Control · Electrical Eng. & Systems 2020-12-18 Jawher Jerray , Laurent Fribourg

In this note we outline the Monte Carlo project {\tt KrkMC}. The goal of this project is to construct a QCD Parton Shower accurate to NLO level in both coefficient function and splitting function (shower) parts. We discuss in detail one of…

High Energy Physics - Phenomenology · Physics 2014-07-24 M. Skrzypek , O. Gituliar , S. Jadach , A. Kusina

We develop a diagrammatic Monte Carlo method for the real-time dynamics of dissipative quantum impurity models. These are small open quantum systems with interaction and local Markovian dissipation, coupled to a large quantum bath. Our…

Strongly Correlated Electrons · Physics 2024-03-26 Matthieu Vanhoecke , Marco Schirò

We introduce a novel Multi-Order Monte Carlo approach for uncertainty quantification in the context of multiscale time-dependent partial differential equations. The new framework leverages Implicit-Explicit Runge-Kutta time integrators to…

Numerical Analysis · Mathematics 2026-04-08 Giulia Bertaglia , Walter Boscheri , Lorenzo Pareschi

Discrepancies play an important role in the study of uniformity properties of point sets. Their probability distributions are a help in the analysis of the efficiency of the Quasi Monte Carlo method of numerical integration, which uses…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. F. W. van Hameren

Quantum Monte Carlo methods are used to calculate various ground state properties of charged bosons in two dimensions, throughout the whole density range where the fluid phase is stable. Wigner crystallization is predicted at $r_s\simeq…

Condensed Matter · Physics 2018-05-01 S. De Palo , S. Conti , S. Moroni

A technique for reducing the number of integrals in a Monte Carlo calculation is introduced. For integrations relying on classical or mean-field trajectories with local weighting functions, it is possible to integrate analytically at least…

Statistical Mechanics · Physics 2024-05-17 Jarod Tall , Steven Tomsovic

In this work we study systems consisting of a group of moving particles. In such systems, often some important parameters are unknown and have to be estimated from observed data. Such parameter estimation problems can often be solved via a…

Applications · Statistics 2023-07-11 Chen Cheng , Linjie Wen , Jinglai Li
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