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We study statistical model checking of continuous-time stochastic hybrid systems. The challenge in applying statistical model checking to these systems is that one cannot simulate such systems exactly. We employ the multilevel Monte Carlo…

Systems and Control · Computer Science 2017-06-27 Sadegh Esmaeil Zadeh Soudjani , Rupak Majumdar , Tigran Nagapetyan

We discuss the efficiency of Monte Carlo methods in solving continuum radiative transfer problems. The sampling of the radiation field and convergence of dust temperature calculations in the case of optically thick clouds are both studied.…

Astrophysics · Physics 2009-11-10 M. Juvela

The Monte Carlo method is the most popular technique to perform radiative transfer simulations in a general 3D geometry. The algorithms behind and acceleration techniques for Monte Carlo radiative transfer are discussed extensively in the…

Instrumentation and Methods for Astrophysics · Physics 2015-05-29 Maarten Baes , Peter Camps

I summarize the successes and failures of the most popular current cosmological models in accounting for the available observations. This evaluation, presented as the summary of the 11th Potsdam Workshop on Large-Scale Structure, was…

Astrophysics · Physics 2007-05-23 Neta A. Bahcall

With Run II of the LHC having started, the need for high precision theory predictions whose uncertainty matches that of the data to be taken necessitated a range of new developments in Monte-Carlo Event Generators. This talk will give an…

High Energy Physics - Phenomenology · Physics 2016-07-20 Marek Schönherr

This paper introduces a novel Monte Carlo (MC) method to simulate the evolution of the low-earth orbit environment, enhancing the MIT Orbital Capacity Analysis Tool (MOCAT). In recent decades, numerous space environment models have been…

Earth and Planetary Astrophysics · Physics 2024-10-15 Daniel Jang , Davide Gusmini , Peng Mun Siew , Andrea D'Ambrosio , Simone Servadio , Pablo Machuca , Richard Linares

Orthogonal Monte Carlo (OMC) is a very effective sampling algorithm imposing structural geometric conditions (orthogonality) on samples for variance reduction. Due to its simplicity and superior performance as compared to its Quasi Monte…

Machine Learning · Computer Science 2020-05-29 Han Lin , Haoxian Chen , Tianyi Zhang , Clement Laroche , Krzysztof Choromanski

This paper is on Bayesian inference for parametric statistical models that are defined by a stochastic simulator which specifies how data is generated. Exact sampling is then possible but evaluating the likelihood function is typically…

Machine Learning · Statistics 2020-03-02 Borislav Ikonomov , Michael U. Gutmann

Accurately and efficiently estimating system performance under uncertainty is paramount in power system planning and operation. Monte Carlo simulation is often used for this purpose, but convergence may be slow, especially when detailed…

Computation · Statistics 2020-10-23 Simon Tindemans , Goran Strbac

In this work we propose a new approach for the numerical simulation of kinetic equations through Monte Carlo schemes. We introduce a new technique which permits to reduce the variance of particle methods through a matching with a set of…

Mathematical Physics · Physics 2014-04-08 Pierre Degond , Giacomo Dimarco , Lorenzo Pareschi

We give a brief review of recent developments by the variational Monte Carlo method, in addition to some new results. We discuss $t$-$J$-type models: the ordinary $t$-$J$ model in one and two dimensions, and the one-dimensional…

Condensed Matter · Physics 2007-05-23 Hisatoshi Yokoyama , Yoshio Kuramoto , Masao Ogata

In this contribution the new event generation framework SHERPA will be presented, which aims at a full simulation of events at current and future high-energy experiments. Some first results exemplify its capabilities.

High Energy Physics - Phenomenology · Physics 2007-05-23 T. Gleisberg , S. Hoeche , F. Krauss , A. Schaelicke , S. Schumann , J. Winter , G. Soff

This presentation will introduce the audience to a new, emerging body of research on sequential Monte Carlo techniques in robotics. In recent years, particle filters have solved several hard perceptual robotic problems. Early successes were…

Robotics · Computer Science 2013-01-07 Sebastian Thrun

Simulating samples from arbitrary probability distributions is a major research program of statistical computing. Recent work has shown promise in an old idea, that sampling from a discrete distribution can be accomplished by perturbing and…

Computation · Statistics 2016-04-13 Chris J. Maddison

Rotoscoping, the detailed delineation of scene elements through a video shot, is a painstaking task of tremendous importance in professional post-production pipelines. While pixel-wise segmentation techniques can help for this task,…

Computer Vision and Pattern Recognition · Computer Science 2016-12-06 Ondrej Miksik , Juan-Manuel Pérez-Rúa , Philip H. S. Torr , Patrick Pérez

The development of multireference coupled cluster (MRCC) techniques has remained an open area of study in electronic structure theory for decades due to the inherent complexity of expressing a multi-configurational wavefunction in the…

Chemical Physics · Physics 2023-05-24 Maria-Andreea Filip , Alex J. W. Thom

This is a status report of the WHIZARD Monte Carlo multi-purpose event generator given at the LCFORUM 2012 at DESY. I review here the development of the WHIZARD generator version 2 with a special emphasis on linear collider physics. In case…

High Energy Physics - Phenomenology · Physics 2012-04-30 Juergen Reuter

Recent progress in the calculation of radiative corrections and in Monte Carlo event generation, relevant for a future e+e- linear collider, is reviewed.

High Energy Physics - Phenomenology · Physics 2007-05-23 Stefan Dittmaier

Resilience is emerging as a key requirement for next-generation wireless communication systems, requiring the ability to assess and control rare, path-dependent failure events arising from sequential degradation and delayed recovery. In…

Systems and Control · Electrical Eng. & Systems 2026-04-02 Onel Luis Alcaraz López