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It is shown that the ratio of factorial cumulant moments to factorial moments for a multiplicity distribution truncated in the tail reveals oscillations in sign similar to those observed in experimental data. It is suggested that this…

High Energy Physics - Phenomenology · Physics 2008-11-26 R. Ugoccioni , A. Giovannini , S. Lupia

We investigate the emergence of long-range correlations in granular shear flow. By increasing the density of a simulated granular flow we observe a spontaneous transition from a dilute regime, where interactions are dominated by binary…

Soft Condensed Matter · Physics 2009-11-11 Gregg Lois , Anael Lemaitre , Jean M. Carlson

The present work proposes the concept of induced percolation over multiple-object systems, so that features such as the number of merged clusters can be used as a relevant measurement. The suggested approach involves the expansion of the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Luciano da Fontoura Costa

Among the best known quantities obtainable from photon correlation measurements are the $g^{(m)}$~correlation functions. Here, we introduce a new procedure to evaluate these correlation functions based on higher-order factorial cumulants…

Mesoscale and Nanoscale Physics · Physics 2022-05-24 Philipp Stegmann , Satyendra Nath Gupta , Gilad Haran , Jianshu Cao

The standard methods for detecting differential gene expression are mostly designed for analyzing a single gene expression experiment. When data from multiple related gene expression studies are available, separately analyzing each study is…

Methodology · Statistics 2013-11-07 Yingying Wei , Hongkai Ji

We analyze the multiplicity correlations between distant forward and backward rapidity regions in relativistic heavy-ion collisions in a superposition framework, where the particle production occurs through independent emission from…

Nuclear Theory · Physics 2015-06-15 Adam Olszewski , Wojciech Broniowski

In multivariate time series systems, key insights can be obtained by discovering lead-lag relationships inherent in the data, which refer to the dependence between two time series shifted in time relative to one another, and which can be…

Machine Learning · Statistics 2023-09-20 Yichi Zhang , Mihai Cucuringu , Alexander Y. Shestopaloff , Stefan Zohren

In this note we discuss subtleties associated with the efficiency corrections for measurements of off-diagonal cumulants and factorial moments for a situation when one deals with overlapping sets of particles, such as correlations between…

Nuclear Theory · Physics 2021-03-18 Volodymyr Vovchenko , Volker Koch

We propose to verify relations between quantities which characterize scaling properties of high energy density fluctuations in terms of factorial moments and newly introduced associated frequency moments. Typical examples are presented in…

High Energy Physics - Phenomenology · Physics 2014-11-17 Mikulaas Blazek

A rewiew of the development of formalism to describe correlations and fluctuations in multiparticle production is presented. The milestones of history of this development and some obvious sources of correlations in experimental data are…

High Energy Physics - Phenomenology · Physics 2007-05-23 K. Fialkowski

Multiplicity distributions exhibit, after closer inspection, peculiarly enhanced void probability and oscillatory behavior of the modified combinants. We discuss the possible sources of these oscillations and their impact on our…

High Energy Physics - Phenomenology · Physics 2019-06-04 Maciej Rybczyński , Grzegorz Wilk , Zbigniew Włodarczyk

Machine learning tools have empowered a qualitatively new way to perform differential cross section measurements whereby the data are unbinned, possibly in many dimensions. Unbinned measurements can enable, improve, or at least simplify…

Various parametrizations of the multiplicity distribution are studied using the recently published large statistics OPAL results on multidimensional local fluctuations and genuine correlations in e+e- -> Z -> hadrons. The measured…

High Energy Physics - Phenomenology · Physics 2009-10-31 Edward K. G. Sarkisyan

Theoretical and experimental studies of high multiplicity events are analyzed. Some interesting phenomena can be revealed at high multiplicities. Preliminary results of project "Thermalization" are reported.

High Energy Physics - Phenomenology · Physics 2007-07-03 E. S. Kokoulina , A. Ya. Kutov , for SVD-2 Collaboration

The multivariate probit is popular for modeling correlated binary data, with an attractive balance of flexibility and simplicity. However, considerable challenges remain in computation and in devising a clear statistical framework. Interest…

Methodology · Statistics 2020-04-22 Bryan W. Ting , Fred A. Wright , Yi-Hui Zhou

We revisit the method of cumulants for analysing dynamic light scattering data in particle sizing applications. Here the data, in the form of the time correlation function of scattered light, is written as a series involving the first few…

Soft Condensed Matter · Physics 2015-04-27 Alastair G. Mailer , Paul S. Clegg , Peter N. Pusey

Multiplicity correlation measurements provide insight into the dynamics of high energy collisions. Models describing these collisions need these correlation measurements to tune the strengths of the underlying QCD processes which influence…

Nuclear Experiment · Physics 2016-04-27 K. Gulbrandsen , C. Soegaard

The multinomial probit model is a typical statistical model for multiple-choice data applied in many research areas. When we are interested in some quantiles of relative utilities for understanding the distribution of these utilities, the…

Methodology · Statistics 2025-08-20 Masaaki Okabe , Koki Matsuoka , Jun Tsuchida , Hiroshi Yadohisa

In light of the widespread success of generative models, a significant amount of research has gone into speeding up their sampling time. However, generative models are often sampled multiple times to obtain a diverse set incurring a cost…

Machine Learning · Computer Science 2023-11-27 Gabriele Corso , Yilun Xu , Valentin de Bortoli , Regina Barzilay , Tommi Jaakkola

Learning multimodal representations is a fundamentally complex research problem due to the presence of multiple heterogeneous sources of information. Although the presence of multiple modalities provides additional valuable information,…

Machine Learning · Computer Science 2019-05-15 Yao-Hung Hubert Tsai , Paul Pu Liang , Amir Zadeh , Louis-Philippe Morency , Ruslan Salakhutdinov