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To reconstruct the impact parameter distributions from the selected events sample or centrality, which is defined by two-observables, at intermediate energy heavy ion collisions, we extend the approach proposed by Das \textit{et al.} [Phys.…

Nuclear Theory · Physics 2023-09-06 Xiang Chen , Li Li , Ying Cui , Junping Yang , Zhuxia Li , Yingxun Zhang

The influence of multiplicity distribution (fluctuation of multiplicity in the event space) on the erraticity behaviour in high energy collisions is investigated via Monte Carlo simulation and compared with the experimental results from…

High Energy Physics - Phenomenology · Physics 2007-05-23 Liu zhixiu , Fu Jinghua , Liu Lianshou

Machine learning models are often used to inform real world risk assessment tasks: predicting consumer default risk, predicting whether a person suffers from a serious illness, or predicting a person's risk to appear in court. Given…

Machine Learning · Computer Science 2023-06-27 Jamelle Watson-Daniels , David C. Parkes , Berk Ustun

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability…

Methodology · Statistics 2013-10-15 Mingyuan Zhou , Lawrence Carin

We study the influence of global baryon number conservation on the non-critical baseline of net baryon cumulants in heavy-ion collisions in a given acceptance, accounting for the asymmetry between the mean-numbers of baryons and…

Proton-proton collisions at new high energies ($\sqrt {s} =$ 2.36 and 7 TeV) at LHC resulted into greater mean multiplicities ($<n>$) of charged particles in the mid-rapidity region than estimated ones by different models and event…

High Energy Physics - Phenomenology · Physics 2012-02-21 Premomoy Ghosh

Matrix completion focuses on recovering missing or incomplete information in matrices. This problem arises in various applications, including image processing and network analysis. Previous research proposed Poisson matrix completion for…

Machine Learning · Computer Science 2024-08-30 Yu Lu , Kevin Bui , Roummel F. Marcia

Negative probabilities arise primarily in physics, statistical quantum mechanics and quantum computing. Negative probabilities arise as mixing distributions of unobserved latent variables in Bayesian modeling. Our goal is to provide a link…

Quantum Physics · Physics 2024-09-06 Nick Polson , Vadim Sokolov

The system size and centrality dependence of multiplicity fluctuations in nuclear collisions at $158A$ GeV as well as the energy dependence for the most central $Pb+Pb$ collisions were studied by the NA49 experiment at CERN SPS. A strong…

Nuclear Experiment · Physics 2016-08-16 Benjamin Lungwitz

The PHENIX Experiment at the Relativistic Heavy Ion Collider has made measurements of event-by-event fluctuations in the net charge, the mean transverse momentum, and the charged particle multiplicity as a function of collision energy,…

Nuclear Experiment · Physics 2009-11-11 J. T. Mitchell

In conjunction with models, the experimental observable total multiplicity can be used to check if the data contain the signature of phase transition and if it is first order. Two of the models reach similar conclusions. The third one is…

Nuclear Theory · Physics 2018-05-09 S Das Gupta , S. Mallik , G. Chaudhuri

We compute the proton-proton multiplicity distributions at LHC energies in the framework of a multiple scattering model assuming a Poisson distribution for each inelastic collision. Multiple scattering is essential to broaden the…

High Energy Physics - Phenomenology · Physics 2013-01-16 A. Capella , E. G. Ferreiro

We discuss two topics on the experimental measurements of fluctuation observables in relativistic heavy-ion collisions. First, we discuss the effects of the thermal blurring, i.e. the blurring effect arising from the experimental…

Nuclear Theory · Physics 2016-10-21 Masakiyo Kitazawa , Masayuki Asakawa

The Poisson-liked statistical fluctuations, which are caused by the finite number of produced particles, are firstly estimated for the cumulants of conserved charges, i.e., the cumulants of net-baryon, net-electric charge, and…

Nuclear Theory · Physics 2014-01-22 Xue Pan , Fan Zhang , Zhiming Li , Lizhu Chen , Mingmei Xu , Yuanfang Wu

We explore net charge probability distributions in heavy ion collisions within the hadron resonance gas model. The distributions for strangeness, electric charge and baryon number are derived. We show that, within this model, net charge…

High Energy Physics - Phenomenology · Physics 2015-06-03 P. Braun-Munzinger , B. Friman , F. Karsch , K. Redlich , V. Skokov

Large-scale multiple testing problems require the simultaneous assessment of many p-values. This paper compares several methods to assess the evidence in multiple binomial counts of p-values: the maximum of the binomial counts after…

Methodology · Statistics 2014-02-26 Guenther Walther

This note presents a refined local approximation for the logarithm of the ratio between the negative multinomial probability mass function and a multivariate normal density, both having the same mean-covariance structure. This…

Statistics Theory · Mathematics 2024-04-04 Christian Genest , Frédéric Ouimet

Baryon number cumulants are invaluable tools to diagnose the primordial stage of heavy ion collisions if they can be measured. In experiments, however, proton number cumulants have been measured as substitutes. In fact, proton number…

Nuclear Theory · Physics 2015-05-28 Masakiyo Kitazawa , Masayuki Asakawa

In this paper, two parametric probability distributions capable to describe the statistics of X-ray photon detection by a CCD are presented. They are formulated from simple models that account for the pile-up phenomenon, in which two or…

Instrumentation and Methods for Astrophysics · Physics 2013-10-30 Diego J. R. Sevilla

An important functional of Poisson random measure is the negative binomial process (NBP). We use NBP to introduce a generalized Poisson-Kingman distribution and its corresponding random discrete probability measure. This random discrete…

Statistics Theory · Mathematics 2023-07-04 Sadegh Chegini , Mahmoud Zarepour
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