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Density ratio estimation (DRE) is a paramount task in machine learning, for its broad applications across multiple domains, such as covariate shift adaptation, causal inference, independence tests and beyond. Parametric methods for…

Machine Learning · Statistics 2025-06-03 Meilin Wang , Wei Huang , Mingming Gong , Zheng Zhang

Experimental data in particle and nuclear physics, particle astrophysics, and radiation protection dosimetry are collected using experimental facilities that consist of a complex system of sensors, electronics, and software. Measured…

Data Analysis, Statistics and Probability · Physics 2026-03-04 Nikolay D. Gagunashvili

We present an extensive numerical study of the time irreversibility of the dynamics of heavy inertial particles in three-dimensional, statistically homogeneous and isotropic turbulent flows. We show that the probability density function…

Fluid Dynamics · Physics 2018-03-07 Akshay Bhatnagar , Anupam Gupta , Dhrubaditya Mitra , Rahul Pandit

We describe a simple method for estimating the vertical column density in Smoothed Particle Hydrodynamics (SPH) simulations of discs. As in the method of Stamatellos et al. (2007), the column density is estimated using pre-computed local…

Instrumentation and Methods for Astrophysics · Physics 2015-06-05 Matthew D. Young , Erik Bertram , Nick Moeckel , Cathie J. Clarke

The current PDF4LHC recommendation to estimate uncertainties due to parton distribution functions (PDFs) in theoretical predictions for LHC processes involves the combination of separate predictions computed using PDF sets from different…

High Energy Physics - Phenomenology · Physics 2015-09-30 Stefano Carrazza , Jose I. Latorre , Juan Rojo , Graeme Watt

We use stochastic computer simulations to study the transport of a spherical cargo particle along a microtubule-like track on a planar substrate by several kinesin-like processive motors. Our newly developed adhesive motor dynamics…

Subcellular Processes · Quantitative Biology 2010-02-24 Christian B. Korn , Stefan Klumpp , Reinhard Lipowsky , Ulrich S. Schwarz

We consider one-dimensional hyperbolic PDEs, linear and nonlinear, with random initial data. Our focus is the {\em pointwise statistics,} i.e., the probability measure of the solution at any fixed point in space and time. For linear…

Analysis of PDEs · Mathematics 2025-12-17 Alina Chertock , Pierre Degond , Amir Sagiv , Li Wang

Recently, a novel approach has been proposed to compute parton distributions through the use of boosted correlators fixed in the Coulomb gauge from lattice QCD, within the framework of Large-Momentum Effective Theory (LaMET). This approach…

High Energy Physics - Lattice · Physics 2026-02-13 Xiang Gao , Jinchen He , Joshua Lin , Swagato Mukherjee , Peter Petreczky , Rui Zhang , Yong Zhao

Numerical evidence of non-diffusive transport in three-dimensional, resistive pressure-gradient-driven plasma turbulence is presented. It is shown that the probability density function (pdf) of test particles' radial displacements is…

Plasma Physics · Physics 2009-11-10 D. del-Castillo-Negrete , B. A. Carreras , V. E. Lynch

The dynamics of a quantum particle bound by an accelerating delta-functional potential is investigated. Three cases are considered, using the reference frame moving along with the {\delta}-function, in which the acceleration is converted…

Quantum Physics · Physics 2015-05-27 Er'el Granot , Boris Malomed

In science and engineering, we often work with models designed for accurate prediction of variables of interest. Recognizing that these models are approximations of reality, it becomes desirable to apply multiple models to the same data and…

Machine Learning · Computer Science 2024-04-03 Marzieh Ajirak , Daniel Waxman , Fernando Llorente , Petar M. Djuric

The human ability to detect and segment moving objects works in the presence of multiple objects, complex background geometry, motion of the observer, and even camouflage. In addition to all of this, the ability to detect motion is nearly…

Computer Vision and Pattern Recognition · Computer Science 2016-04-04 Pia Bideau , Erik Learned-Miller

Joint probability density function (PDF)-based models in turbulent combustion provide direct closure for turbulence-chemistry interactions. The joint PDFs capture the turbulent flame dynamics at different spatial locations and hence it is…

Fluid Dynamics · Physics 2021-04-06 Rishikesh Ranade , Kevin Gitushi , Tarek Echekki

We report a joint experimental and theoretical investigation of the probability distribution functions (pdf's) of the normal and tangential (frictional) forces in amorphous frictional media. We consider both the joint pdf of normal and…

Soft Condensed Matter · Physics 2018-07-25 V. S. Akella , M. M. Bandi , H. George E. Hentschel , Itamar Procaccia , Saikat Roy

The one-point probability distribution function (PDF) of the matter density field in the universe is a fundamental property that plays an essential role in cosmology for estimates such as gravitational weak lensing, non-linear clustering,…

Cosmology and Nongalactic Astrophysics · Physics 2018-10-10 Anatoly Klypin , Francisco Prada , Juan Betancort-Rijo , Franco D. Albareti

Probability density estimation is a core problem of statistics and signal processing. Moment methods are an important means of density estimation, but they are generally strongly dependent on the choice of feasible functions, which severely…

Machine Learning · Statistics 2023-07-06 Guangyu Wu , Anders Lindquist

At any given scale, 3$\times$2-point statistics extract only three numbers from the joint distribution of the cosmic matter density and galaxy density fluctuations: their variances and their covariance. It is well known that the full shape…

Cosmology and Nongalactic Astrophysics · Physics 2026-01-07 Oliver Friedrich , Lina Castiblanco , Anik Halder , Cora Uhlemann

We quantitatively study the probability distribution function (PDF) of cosmological nonlinear density fluctuations from N-body simulations with Gaussian initial condition. In particular, we examine the validity and limitations of one-point…

Astrophysics · Physics 2009-11-06 Issha Kayo , Atsushi Taruya , Yasushi Suto

We generalize Einstein's probabilistic method for the Brownian motion to study compressible fluids in porous media. The multi-dimensional case is considered with general probability distribution functions. By relating the expected…

Analysis of PDEs · Mathematics 2025-03-06 Luan Hoang , Akif Ibragimov

Under some weak conditions, the first-passage time of the Brownian motion to a continuous curved boundary is an almost surely finite stopping time. Its probability density function (pdf) is explicitly known only in few particular cases.…

Probability · Mathematics 2016-01-22 Samuel Herrmann , Etienne Tanré