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We introduce the response function (RFs) approach to model the weak lensing statistics in the context of separate universe formalism. Numerical results for the RFs are presented for various semi-analytical models that include perturbative…

Cosmology and Nongalactic Astrophysics · Physics 2022-10-26 D. Munshi , R. Takahashi , J. D. McEwen

We reexamine results obtained with the recently proposed density functional theory framework based on forces (force-DFT) [Tschopp et al., Phys. Rev. E 106, 014115 (2022)]. We compare inhomogeneous density profiles for hard sphere fluids to…

Soft Condensed Matter · Physics 2024-02-28 Florian Sammüller , Sophie Hermann , Matthias Schmidt

We introduce a method for calculating the probability density function (PDF) of a turbulent density field in three dimensions using only information contained in the projected two-dimensional column density field. We test the method by…

Astrophysics of Galaxies · Physics 2015-05-18 Christopher M. Brunt , Christoph Federrath , Daniel J. Price

Assuming we have iid observations from two unknown probability density functions (pdfs), $p$ and $q$, the likelihood-ratio estimation (LRE) is an elegant approach to compare the two pdfs only by relying on the available data. In this paper,…

Machine Learning · Statistics 2024-02-02 Alejandro de la Concha , Nicolas Vayatis , Argyris Kalogeratos

Modeling large dependent datasets in modern time series analysis is a crucial research area. One effective approach to handle such datasets is to transform the observations into density functions and apply statistical methods for further…

Methodology · Statistics 2025-07-23 Yinzhi Wang , Yingqiu Zhu , Ben-Chang Shia , Lei Qin

Stochastic gradient descent (SGD) and its variants have established themselves as the go-to algorithms for large-scale machine learning problems with independent samples due to their generalization performance and intrinsic computational…

Machine Learning · Statistics 2025-08-25 Hao Chen , Lili Zheng , Raed Al Kontar , Garvesh Raskutti

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 paper, we present a novel approach termed Prompt-Driven Feature Diffusion (PDFD) within a semi-supervised learning framework for Open World Semi-Supervised Learning (OW-SSL). At its core, PDFD deploys an efficient feature-level…

Machine Learning · Computer Science 2024-04-19 Marzi Heidari , Hanping Zhang , Yuhong Guo

We present NNPDFpol2.0, a new set of collinear helicity parton distribution functions (PDFs) of the proton based on legacy measurements of structure functions in inclusive neutral-current longitudinally polarised deep-inelastic scattering…

Weak lensing measurements are starting to provide statistical maps of the distribution of matter in the universe that are increasingly precise and complementary to cosmic microwave background maps. The probability distribution (PDF)…

Astrophysics · Physics 2009-11-10 Tong-Jie Zhang , Ue-Li Pen

This paper presents a novel approach to measuring statistical dependence between two random processes (r.p.) using a positive-definite function called the Normalized Cross Density (NCD). NCD is derived directly from the probability density…

Machine Learning · Computer Science 2024-02-22 Bo Hu , Jose C. Principe

The estimation and utilization of photometric redshift probability density functions (photo-$z$ PDFs) has become increasingly important over the last few years and currently there exist a wide variety of algorithms to compute photo-$z$'s,…

Cosmology and Nongalactic Astrophysics · Physics 2014-06-05 M. Carrasco Kind , R. J. Brunner

This article is a survey of results concerning an inequality, which may be seen as a versatile tool to solve problems in the domain of Applied Probability. The inequality, which we call BRS-inequality, gives a convenient upper bound for the…

Probability · Mathematics 2020-07-13 F. Thomas Bruss

Density Functional Theory (DFT) is one of the most widely used methods for "ab initio" calculations of the structure of atoms, molecules, crystals, surfaces, and their interactions. Unfortunately, the customary introduction to DFT is often…

Physics Education · Physics 2010-12-07 Nathan Argaman , Guy Makov

Despite the high accuracy of photometric redshifts (zphot) derived using Machine Learning (ML) methods, the quantification of errors through reliable and accurate Probability Density Functions (PDFs) is still an open problem. First, because…

A probabilistic circuit (PC) succinctly expresses a function that represents a multivariate probability distribution and, given sufficient structural properties of the circuit, supports efficient probabilistic inference. Typically a PC…

Machine Learning · Computer Science 2024-08-09 Oliver Broadrick , William Cao , Benjie Wang , Martin Trapp , Guy Van den Broeck

Context: Statistical properties of the cosmic density fields are to a large extent encoded in the shape of the one-point density probability distribution functions (PDF). In order to successfully exploit such observables, a detailed…

Cosmology and Nongalactic Astrophysics · Physics 2022-07-20 Francis Bernardeau

Recently, it was shown that the probability distribution function (PDF) of the free energy of a single continuum directed polymer (DP) in a random potential, equivalently of the height of a growing interface described by the…

Statistical Mechanics · Physics 2017-03-29 Andrea De Luca , Pierre Le Doussal

Relative Divergence (RD) and Maximum Relative Divergence Principle (MRDP) for grading (order-comonotonic) functions (GF) on posets are used as an expression of Insufficient Reason Principle under the given prior information (IRP+). Classic…

Information Theory · Computer Science 2025-10-07 Alexander Dukhovny

Perturbation theory makes it possible to calculate the probability distribution function (PDF) of the large scale density field in the small variance limit. For top hat smoothing and scale-free Gaussian initial fluctuations, the result…

Astrophysics · Physics 2015-06-24 S. Colombi , F. Bernardeau , F. R. Bouchet , L. Hernquist