Related papers: Note on the CMS multiplicity distributions
We present the results for the evolution of transverse momentum spectra for the jetty and underlying parts of events as a function of multiplicity in pp collisions at 13 TeV measured at midrapidity ($\left|\eta\right|<0.8$) using PYTHIA8…
The study of femtoscopic correlations in high-energy collisions is a powerful tool to investigate the space-time structure of the particle emitting region formed in such collisions, as well as to probe interactions that the involved…
We study the differences in the gamma ray spectra simulated by four Monte Carlo event generator packages developed in particle physics. Two different versions of PYTHIA and two of HERWIG are analyzed, namely PYTHIA 6.418 and HERWIG 6.5.10…
The negative binomial distribution has been widely used as a more flexible model than the Poisson distribution for count data. However, when the true data-generating process is Poisson, it is often challenging to distinguish it from a…
In the present paper we demonstrate the results of a statistical analysis of some characteristics of precipitation events and propose a kind of a theoretical explanation of the proposed models in terms of mixed Poisson and mixed exponential…
Event classifiers based either on the charged-particle multiplicity or the event shape have been extensively used in proton-proton (pp) collisions by the ALICE collaboration at the LHC. The use of these tools became very instrumental since…
We present MultiGain, a tool to synthesize strategies for Markov decision processes (MDPs) with multiple mean-payoff objectives. Our models are described in PRISM, and our tool uses the existing interface and simulator of PRISM. Our tool…
Categorical data are often observed as counts resulting from a fixed number of trials in which each trial consists of making one selection from a prespecified set of categories. The multinomial distribution serves as a standard model for…
Considerable interest has recently been focused on studying multiple phenotypes simultaneously in both epidemiological and genomic studies, either to capture the multidimensionality of complex disorders or to understand shared etiology of…
Subthreshold events (pion production, for instance) at energies $E< m_{\pi}$ are treated as rare events. The associated multiplicity distribution $P_c (n)$ and the unconstrained distribution P(n), when there is no rare event-trigger, are…
We propose a general approach for the description of multijet events in the framework of QCD event generators. We introduce a new algorithm to match parton showers and arbitrary matrix elements for the production of any number of jets via…
The solution of QCD equations for generating functions of {\it parton} multiplicity distributions reveals new peculiar features of cumulant moments oscillating as functions of their rank. It happens that experimental data on {\it hadron}…
This paper introduces Bayesian frameworks for tackling various aspects of multi-criteria decision-making (MCDM) problems, leveraging a probabilistic interpretation of MCDM methods and challenges. By harnessing the flexibility of Bayesian…
This paper proposes a form of MPC in which the control variables are moved asynchronously. This contrasts with most MIMO control schemes, which assume that all variables are updated simultaneously. MPC outperforms other control strategies…
Measurements of Underlying Event activity using proton-proton collision data collected by the CMS detector will be presented. To check the energy dependence of the underlying event activity, results are compared with previous measurements…
This paper studies integral-type event-triggered model predictive control (MPC) of continuous-time nonlinear systems. An integral-type event-triggered mechanism is proposed by incorporating the integral of errors between the actual and…
In this article, we proposed a new probability distribution named as power Maxwell distribution (PMaD). It is another extension of Maxwell distribution (MaD) which would lead more flexibility to analyze the data with non-monotone failure…
Event-triggered control is often argued to lower the average triggering rate compared to time-triggered control while still achieving a desired control goal, e.g., the same performance level. However, this property, often called…
Cumulative probability models (CPMs) are a robust alternative to linear models for continuous outcomes. However, they are not feasible for very large datasets due to elevated running time and memory usage, which depend on the sample size,…
Machine learning systems increasingly depend on pipelines of multiple algorithms to provide high quality and well structured predictions. This paper argues interaction effects between clustering and prediction (e.g. classification,…