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This Letter provides a theoretical interpretation of numerically generated probability density functions (PDFs) of intermittent plasma transport events. Specifically, nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence…

Plasma Physics · Physics 2010-11-10 Johan Anderson , Pavlos Xanthopoulos

Employing the formalism introduced by Sinai and Yakhot [PRL, 63(18), p. 1962, 1989], we study the probability density functions (pdf's) of decaying passive scalars in periodic domains under the influence of smooth large scale velocity…

Chaotic Dynamics · Physics 2009-11-10 Jai Sukhatme

The two-parameter distribution known as exponential-Poisson (EP) distribution, which has decreasing failure rate, was introduced by Kus (2007). In this paper we generalize the EP distribution and show that the failure rate of the new…

Methodology · Statistics 2010-08-17 Wagner Barreto-Souza , Francisco Cribari-Neto

The probability density function (PDF) of some global average quantity plays a fundamental role in critical and highly correlated systems. We explicitly compute this quantity as a function of the magnetization for the two dimensional XY…

High Energy Physics - Lattice · Physics 2009-12-03 G. Palma , D. Zambrano

We compute the joint probability density function (jpdf) P_N(M, \tau_M) of the maximum M and its position \tau_M for N non-intersecting Brownian excursions, on the unit time interval, in the large N limit. For N \to \infty, this jpdf is…

Mathematical Physics · Physics 2015-06-04 Gregory Schehr

Integral and derivative dispersion relations (DR) are considered for the $pp$ and $\bar pp$ forward scattering amplitudes. A new representation for the derivative DR, valid at lower energies than the standard one, is obtained. The data on…

High Energy Physics - Phenomenology · Physics 2007-05-23 J. R. Cudell , E. Martynov , O. V. Selyugin

Parton distribution functions (PDFs) at large $x$ are challenging to extract from experimental data, yet they are essential for understanding hadron structure and searching for new physics beyond the Standard Model. Within the framework of…

High Energy Physics - Phenomenology · Physics 2025-03-03 Xiangdong Ji , Yizhuang Liu , Yushan Su , Rui Zhang

This paper considers the secrecy performance of several schemes for multi-antenna transmission to single-antenna users with full-duplex (FD) capability against randomly distributed single-antenna eavesdroppers (EDs). These schemes and…

Information Theory · Computer Science 2025-07-21 Ishmam Zabir , Ahmed Maksud , Gaojie Chen , Brian M. Sadler , Yingbo Hua

We consider a variant of the channel simulation problem with a single input and multiple outputs, where Alice observes a probability distribution $P$ from a set of prescribed probability distributions $\mathbb{\mathcal{P}}$, and sends a…

Information Theory · Computer Science 2021-09-07 Chak Fung Choi , Cheuk Ting Li

We study the one-point probability distribution functions (PDFs) of the peculiar velocity and the density fluctuation in a cosmological fluid. Within the perturbative approach to the structure formation scenario, the effect of ``pressure''…

Astrophysics · Physics 2009-11-11 Takayuki Tatekawa

Lagrangian stochastic methods are widely used to model turbulent flows. Scarce consideration has, however, been devoted to the treatment of the near-wall region and to the formulation of a proper wall-boundary condition. With respect to…

Fluid Dynamics · Physics 2024-02-07 Guilhem Balvet , Jean-Pierre Minier , Yelva Roustan , Martin Ferrand

Probabilistic shaping for intensity modulation and direct detection (IM/DD) links is discussed and a peak power constraint determined by the limited modulation extinction ratio (ER) of optical modulators is introduced. The input…

Information Theory · Computer Science 2021-02-03 Thomas Wiegart , Francesco Da Ros , Metodi Plamenov Yankov , Fabian Steiner , Simone Gaiarin , Richard Wesel

Fusing probabilistic information is a fundamental task in signal and data processing with relevance to many fields of technology and science. In this work, we investigate the fusion of multiple probability density functions (pdfs) of a…

Signal Processing · Electrical Eng. & Systems 2023-01-20 Günther Koliander , Yousef El-Laham , Petar M. Djurić , Franz Hlawatsch

A probability density function (PDF) of a spatially dependent field provides a means of calculating moments of the field or, equivalently, the proportion of a spatial domain that is mapped to a given set of values. This paper describes a…

Fluid Dynamics · Physics 2025-01-10 Paul M. Mannix , David A. Ham , John Craske

This letter describes a direct method for computing the spatially averaged outage probability of a network with interferers located according to a point process and signals subject to fading. Unlike most common approaches, it does not…

Information Theory · Computer Science 2014-04-24 Matthew C. Valenti , Don Torrieri , Salvatore Talarico

Paper [1] derived the probability density function (PDF) of a sum of products of two correlated complex Gaussian zero-mean random variables (RVs) that has been applied to calculate the error probabilities of a \emph{M}-ary phase shift…

Signal Processing · Electrical Eng. & Systems 2019-10-09 Trung-Hien Nguyen , Jerome Louveaux , Philippe De Doncker , Francois Horlin

We study the effect on the parton distribution functions (PDFs) from the inclusion of projected measurements in the Drell-Yan (DY) di-lepton production neutral channel of the angular coefficient associated to the $Z$-boson longitudinal…

High Energy Physics - Phenomenology · Physics 2021-10-06 Juri Fiaschi

In this work, one proposes the use of a damped confinement potential to mimic the proton internal energy. The internal pressure is calculated taking into account the occurrence of a phase transition in the $pp$ and $\bar{p}p$ total cross…

High Energy Physics - Phenomenology · Physics 2019-04-19 S. D. Campos

Tensor-network techniques have enjoyed outstanding success in physics, and have recently attracted attention in machine learning, both as a tool for the formulation of new learning algorithms and for enhancing the mathematical understanding…

Machine Learning · Computer Science 2019-12-02 Ivan Glasser , Ryan Sweke , Nicola Pancotti , Jens Eisert , J. Ignacio Cirac

Transverse and longitudinal electroweak gauge boson parton distribution functions (PDFs) are computed in terms of deep-inelastic scattering structure functions, following the recently developed method to determine the photon PDF. The…

High Energy Physics - Phenomenology · Physics 2018-05-18 Bartosz Fornal , Aneesh V. Manohar , Wouter J. Waalewijn