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We use a density functional theoretical approach to calculate the pair distribution function and the effective interactions in homogeneous fluids of spinless charged bosons. The scheme involves the self-consistent solution of a two-particle…

Soft Condensed Matter · Physics 2009-11-07 B. Davoudi , R. Asgari , M. Polini , M. P. Tosi

We examine the dependence of parton distribution functions (PDFs) on the value of the QCD coupling strength $\alpha_{s}(M_{Z})$. We explain a simple method that is rigorously valid in the quadratic approximation normally applied in PDF…

High Energy Physics - Phenomenology · Physics 2014-11-20 Hung-Liang Lai , Joey Huston , Zhao Li , Pavel Nadolsky , Jon Pumplin , Daniel Stump , C. -P. Yuan

We construct a set of parton distribution functions (PDFs) in which fixed-order NLO and NNLO calculations are supplemented with soft-gluon (threshold) resummation up to NLL and NNLL accuracy respectively, suitable for use in conjunction…

High Energy Physics - Phenomenology · Physics 2015-10-13 Marco Bonvini , Simone Marzani , Juan Rojo , Luca Rottoli , Maria Ubiali , Richard D. Ball , Valerio Bertone , Stefano Carrazza , Nathan P. Hartland

A probability density function (pdf) encodes the entire stochastic knowledge about data distribution, where data may represent stochastic observations in robotics, transition state pairs in reinforcement learning or any other empirically…

Machine Learning · Computer Science 2018-09-18 Dmitry Kopitkov , Vadim Indelman

The neutrino deep inelastic scattering (DIS) data is very interesting for global analyses of proton and nuclear parton distribution functions (PDFs) since they provide crucial information on the strange quark distribution in the proton and…

High Energy Physics - Phenomenology · Physics 2011-11-07 K. Kovarik , I. Schienbein , F. I. Olness , J. Y. Yu , C. Keppel , J. G. Morfin , J. F. Owens , T. Stavreva

We study the prospects for constraining the nuclear parton distribution functions by small-x deep inelastic scattering. Performing a global fit of nuclear parton distribution functions including a sample of pseudodata representing expected…

High Energy Physics - Phenomenology · Physics 2019-08-14 Hannu Paukkunen , Kari J. Eskola , Néstor Armesto

The increasing scientific and technological interest in nanoparticles has raised the need for fast, efficient and precise characterization techniques. Powder diffraction is a very efficient experimental method, as it is straightforward and…

Materials Science · Physics 2008-12-02 A. Cervellino , C. Giannini , A. Guagliardi , M. Ladisa

Extracting quantitative information about highly scattering surfaces from an imaging system is challenging because the phase of the scattered light undergoes multiple folds upon propagation, resulting in complex speckle patterns. One…

If two probability density functions (PDFs) have values for their first $n$ moments which are quite close to each other (upper bounds of their differences are known), can it be expected that the PDFs themselves are very similar? Shown below…

Statistics Theory · Mathematics 2018-08-16 Pranava Chaitanya Jayanti , Konstantina Trivisa

In this paper, we extend a recently developed machine-learning (ML) based CREASE-2D method to analyze the entire two-dimensional (2D) scattering pattern obtained from small angle X-ray scattering measurements of supramolecular dipeptide…

Soft Condensed Matter · Physics 2025-04-08 Nitant Gupta , Sri V. V. R. Akepati , Simona Bianco , Jay Shah , Dave J. Adams , Arthi Jayaraman

We perform the analysis of the existing inclusive deep inelastic scattering (DIS) data within NNLO QCD approximation. The parton distributions functions (PDFs) and the value of strong coupling constant $\alpha_{s}(M_Z)=0.1143\pm0.0013…

High Energy Physics - Phenomenology · Physics 2015-06-25 Alekhin Sergey

The streaming model describes the mapping between real and redshift space for 2-point clustering statistics. Its key element is the probability density function (PDF) of line-of-sight pairwise peculiar velocities. Following a kinetic-theory…

Cosmology and Nongalactic Astrophysics · Physics 2018-07-24 Joseph Kuruvilla , Cristiano Porciani

As part of a consortium between academic and industry, this PhD work investigates the interest and capabilities of organic photo-sensors (OPS) for the optical characterization of suspensions and two-phase flows. The principle of new optical…

Optics · Physics 2015-03-16 Matthias Sentis

Continuously comparing theory predictions to experimental data is a common task in analysis of particle physics such as fitting parton distribution functions (PDFs). However, typically, both the computation of scattering amplitudes and the…

High Energy Physics - Phenomenology · Physics 2023-03-14 Andrea Barontini , Alessandro Candido , Juan M. Cruz-Martinez , Felix Hekhorn , Christopher Schwan

We present recent progress within the NNPDF parton analysis framework. After a brief review of the results from the DIS NNPDF analysis, NNPDF1.0, we discuss results from an updated analysis with independent parametrizations for the strange…

I review recent progress in the NNPDF global analyses of parton distributions (PDFs) focusing on developments contributing to its new upcoming release: NNPDF4.0. The NNPDF4.0 determination represents unprecedented progress in three main…

High Energy Physics - Phenomenology · Physics 2021-04-20 Juan Rojo

We present a compression algorithm for parton densities using synthetic replicas generated from the training of a Generative Adversarial Network (GAN). The generated replicas are used to further enhance the statistics of a given Monte Carlo…

High Energy Physics - Phenomenology · Physics 2021-07-07 Stefano Carrazza , Juan M. Cruz-Martinez , Tanjona R. Rabemananjara

The parallel sessions of the working group 3 were devoted to the discussions of short-baseline neutrino physics program at neutrino factories. First, possible studies of parton distribution functions (PDFs), in particular nuclear and…

High Energy Physics - Phenomenology · Physics 2008-11-26 A. L. Kataev , S. Kumano

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 recently developed "Data Set Diagonalization" method (DSD) is applied to measure compatibility of the data sets that are used to determine parton distribution functions (PDFs). Discrepancies among the experiments are found to be…

High Energy Physics - Phenomenology · Physics 2010-04-22 Jon Pumplin