Related papers: SIMDET - Version 4 A Parametric Monte Carlo for a …
Pomsets are a promising formalism for concurrent programs based on partially ordered sets. Among this class, series-parallel pomsets admit a convenient linear representation and can be recognized by simple algebraic structures known as…
Accurate knowledge of the response of the detection system is very crucial for unambiguous interpretation of the experimental data. A simulation code has been developed using the Monte Carlo technique involving 3-body kinematics for the…
The Monte Carlo (MC) setups used by ATLAS to model boson$+\mathrm{jets}$ and multi-boson processes at $\sqrt{s}$ = 13 TeV in proton-proton collisions are described. Comparisons between data and several event generators are provided for key…
We present an adaptive multilevel Monte Carlo (AMLMC) algorithm for approximating deterministic, real-valued, bounded linear functionals that depend on the solution of a linear elliptic PDE with a lognormal diffusivity coefficient and…
We introduce a new simplified fast detector simulator in the MadAnalysis 5 platform. The Python-like interpreter of the programme has been augmented by new commands allowing for a detector parametrisation through smearing and efficiency…
Combining electrostatic field simulations with Monte Carlo methods enables realistic modeling of the detector response for novel monolithic silicon detectors with strongly non-linear electric fields. Both the precise field description and…
Super-Droplet Method (SDM) is a probabilistic Monte-Carlo-type model of particle coagulation process, an alternative to the mean-field formulation of Smoluchowski. SDM as an algorithm has linear computational complexity with respect to the…
Propositional bounded model checking has been applied successfully to verify embedded software but is limited by the increasing propositional formula size and the loss of structure during the translation. These limitations can be reduced by…
This work describes the development of different models to detect patronising and condescending language within extracts of news articles as part of the SemEval 2022 competition (Task-4). This work explores different models based on the…
The purpose of the PandaX experiments is to search for the possible events resulted from dark matter particles, neutrinoless double beta decay or other rare processes with xenon detectors. Understanding the energy depositions from…
SUSYGEN is a Monte Carlo program designed for computing distributions and generating events for MSSM sparticle production in e+ e- collisions. The Supersymmetric (SUSY) mass spectrum may either be supplied by the user, or can alternatively…
Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols, and the development or assessment of image reconstruction algorithms…
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…
We present megas, a new software tool that improves the simulation of the Micromegas gas detectors. Our tool offers the possibility to configure multiple arrangements with one or more layers of MM detectors. A series of simple commands can…
NuSD: Neutrino Segmented Detector is a Geant4-based user application that simulates inverse beta decay event in a variety of segmented scintillation detectors developed by different international collaborations. This simulation framework…
Decision Trees are prominent prediction models for interpretable Machine Learning. They have been thoroughly researched, mostly in the batch setting with a fixed labelled dataset, leading to popular algorithms such as C4.5, ID3 and CART.…
We present ImpCresst, a Geant4-based Monte Carlo tool to simulate backgrounds from natural and cosmogenic radionuclides, and calibration signals in solid-state detectors and their response to it. It is tuned for a fast-evolving and…
Radiation effects analysis of instruments operative in harsh radiation environment is crucial for performance and functionality of electronic devices and components. Engineering design of instruments is usually carried out in Computer Aided…
The EM algorithm is a method for finding the maximum likelihood estimate of a model in the presence of missing data. Unfortunately, EM does not produce a parameter covariance matrix for standard errors. Supplemented EM (SEM; Meng & Rubin,…
Modern cars exist in an vast number of variants. Thus, variability has to be dealt with in all phases of the development process, in particular during model-based development of software-intensive functionality using Matlab/Simulink.…