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We revisit the Lieb-Liniger model for $n$ bosons in one dimension with attractive delta interaction in a half-space $\mathbb{R}^+$ with diagonal boundary conditions. This model is integrable for arbitrary value of $b \in \mathbb{R}$, the…

Statistical Mechanics · Physics 2020-06-24 Jacopo De Nardis , Alexandre Krajenbrink , Pierre Le Doussal , Thimothée Thiery

The time evolution of the probability density function (PDF) of the mass density is formulated and solved for systems in free-fall using a simple appoximate function for the collapse of a sphere. We demonstrate that a pressure-free collapse…

Astrophysics of Galaxies · Physics 2015-06-17 Philipp Girichidis , Lukas Konstandin , Anthony P. Whitworth , Ralf S. Klessen

We conduct numerical experiments to determine the density probability distribution function (PDF) produced in supersonic, isothermal, self-gravitating turbulence of the sort that is ubiquitous in star-forming molecular clouds. Our…

Astrophysics of Galaxies · Physics 2021-08-10 Shivan Khullar , Christoph Federrath , Mark R. Krumholz , Christopher D. Matzner

Two conditional averages for the longitudinal velocity increment u_r of the simulated turbulence are calculated: h(u_r) is the average of the increment of the longitudinal Laplacian velocity field with u_r fixed, while g(u_r) is the…

The possibility to apply phase-space methods to many-body interacting systems might provide accurate descriptions of correlations with a reduced numerical cost. For instance, the so--called stochastic mean-field phase-space approach, where…

Nuclear Theory · Physics 2020-04-22 Thomas Czuba , Denis Lacroix , David Regnier , Ibrahim Ulgen , Bulent Yilmaz

Diffusion models indirectly estimate the probability density over a data space, which can be used to study its structure. In this work, we show that geodesics can be computed in diffusion latent space, where the norm induced by the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Qingtao Yu , Jaskirat Singh , Zhaoyuan Yang , Peter Henry Tu , Jing Zhang , Hongdong Li , Richard Hartley , Dylan Campbell

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

High-dimensional data often arise from clinical genomics research to infer relevant predictors of a particular trait. A way to improve the predictive performance is to include information on the predictors derived from prior knowledge or…

Methodology · Statistics 2023-03-13 Claudio Busatto , Mark van de Wiel

This article presents a rigorous analysis for efficient statistically accurate algorithms for solving the Fokker-Planck equations associated with high-dimensional nonlinear turbulent dynamical systems with conditional Gaussian structures.…

Statistics Theory · Mathematics 2017-09-19 Nan Chen , Andrew J. Majda , Xin T. Tong

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

This work is an attempt to transfer to biology the methods developed in physics for formulating and solving the kinetic equations in which the kernel of the integral operator in spatial coordinates is slowly decreasing with increasing…

Quantitative Methods · Quantitative Biology 2020-07-14 A. B. Kukushkin , A. A. Kulichenko , A. V. Sokolov

This paper analyzes a method to approximate the first passage time probability density function which turns to be particularly useful if only sample data are available. The method relies on a Laguerre-Gamma polynomial approximation and…

Probability · Mathematics 2022-12-14 Elvira Di Nardo , Giuseppe D'Onofrio , Tommaso Martini

The Vlasov-Fokker-Planck equation describes the evolution of the probability density of the position and velocity of particles under the influence of external confinement, interaction, friction, and stochastic force. It is well-known that…

Analysis of PDEs · Mathematics 2025-01-16 Sangmin Park

A short review of the currently available modern parton distribution functions (PDFs)and the theory predictions obtained using those PDFs for several benchmark processes at LHC, including Higgs boson production, is presented in this…

High Energy Physics - Phenomenology · Physics 2016-09-23 Ringaile Placakyte

We consider the early time regime of the Kardar-Parisi-Zhang (KPZ) equation in $1+1$ dimensions in curved (or droplet) geometry. We show that for short time $t$, the probability distribution $P(H,t)$ of the height $H$ at a given point $x$…

Statistical Mechanics · Physics 2017-04-26 Pierre Le Doussal , Satya N. Majumdar , Alberto Rosso , Gregory Schehr

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

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 present numerical results obtained from Time-Dependent Density Functional calculations of the dynamics of liquid He-4 in different environments characterized by geometrical confinement. The time-dependent density profile and velocity…

Condensed Matter · Physics 2009-11-07 Luigi Giacomazzi , Flavio Toigo , Francesco Ancilotto

The health condition of components in civil infrastructures can be described by various discrete states according to their performance degradation. Inferring these states from measurable responses is typically an ill-posed inverse problem.…

Machine Learning · Statistics 2026-04-30 Teng Li , Stephen Wu , Yong Huang , James L. Beck , Hui Li

In statistical modeling with Gaussian Process regression, it has been shown that combining (few) high-fidelity data with (many) low-fidelity data can enhance prediction accuracy, compared to prediction based on the few high-fidelity data…

Machine Learning · Statistics 2019-04-23 Seungjoon Lee , Felix Dietrich , George E. Karniadakis , Ioannis G. Kevrekidis