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We present a new method to extract parton distribution functions from high energy experimental data based on a specific type of neural networks, the Self-Organizing Maps. We illustrate the features of our new procedure that are particularly…

High Energy Physics - Phenomenology · Physics 2017-08-23 K. Holcomb , S. Liuti , D. Z. Perry

We propose and analyze a regularization approach for structured prediction problems. We characterize a large class of loss functions that allows to naturally embed structured outputs in a linear space. We exploit this fact to design…

Machine Learning · Computer Science 2017-07-31 Carlo Ciliberto , Alessandro Rudi , Lorenzo Rosasco

Regularisation allows one to handle ill-posed inverse problems. Here we focus on discrete unfolding problems. The properties of the results are characterised by the consistency between measurements and unfolding result and by the posterior…

Data Analysis, Statistics and Probability · Physics 2023-09-07 Michael Schmelling

Parton distribution functions are key quantities for us to understand the hadronic structures in high-energy scattering, but they are difficult to calculate from lattice QCD. Recent years have seen fast development of the large-momentum…

High Energy Physics - Phenomenology · Physics 2019-04-29 Yong Zhao

In this work, standard methods of the mixed thin-shell foramlism are refined using the framework of Colombeau's theory of generalized functions. To this end, systematic use is made of smooth generalized functions, in particular…

General Relativity and Quantum Cosmology · Physics 2025-05-07 Albert Huber

Assuming an effective quadratic Hamiltonian, we derive an approximate, linear stochastic equation of motion for the density-fluctuations in liquids, composed of overdamped Brownian particles. From this approach, time dependent two point…

Soft Condensed Matter · Physics 2017-04-26 Matthias Krüger , David S. Dean

Regularization is a central tool for addressing ill-posedness in inverse problems and statistical estimation, with the choice of a suitable penalty often determining the reliability and interpretability of downstream solutions. While recent…

Optimization and Control · Mathematics 2025-10-07 Oscar Leong , Eliza O'Reilly , Yong Sheng Soh

We present the complete 1-loop perturbative computation of the renormalization constants and mixing coefficients of the operators that measure the first moment of deep inelastic scattering structure functions, employing the nearest neighbor…

High Energy Physics - Lattice · Physics 2009-10-22 Stefano Capitani , Giancarlo Rossi

We present very simple non-integral relations between deep inelastic structure functions $F_L$, $F_2$ and the gluon distribution at small $x$ based on perturbative QCD which are useful for the phenomenological analysis of data at low $x$.…

High Energy Physics - Phenomenology · Physics 2007-05-23 G. Parente , A. V. Kotikov

The importance of properly taking into account the factorization scheme dependence of parton distribution functions is emphasized. A serious error in the usual handling of this topic is pointed out and the correct procedure for transforming…

High Energy Physics - Phenomenology · Physics 2016-08-14 J. Chýla

We attempt to describe the stress distributions of granular packings using lattice-based layer-by-layer stochastic models that satisfy the constraints of force and torque balance and non-tensile forces at each site. The inherent asymmetry…

Soft Condensed Matter · Physics 2009-10-31 M. L. Nguyen , S. N. Coppersmith

Herein we develop a dynamical foundation for fractional Brownian Motion. A clear relation is established between the asymptotic behaviour of the correlation function and diffusion in a dynamical system. Then, assuming that scaling is…

chao-dyn · Physics 2008-02-03 R Mannella , P Grigolini , BJ West

Level and wavefunction statistics have been studied for two dimensional clusters of the square lattice in the presence of random magnetic fluxes. Fluxes traversing lattice plaquettes are distributed uniformly between - (1/2) Phi_0 and (1/2)…

Condensed Matter · Physics 2009-10-28 J. A. Verges

The von Mises-Fisher (vMF) distribution has long been a mainstay for inference with data on the unit hypersphere in directional statistics. The performance of statistical inference based on the vMF distribution, however, may suffer when…

Methodology · Statistics 2025-04-23 Kisung You , Dennis Shung

A density functional theory (DFT) of lattice fermion models is presented, which uses the single-particle density matrix gamma_{ij} as basic variable. A simple, explicit approximation to the interaction-energy functional W[gamma] of the…

Strongly Correlated Electrons · Physics 2009-11-07 R. Lopez-Sandoval , G. M. Pastor

The lattice dynamics of the metallic tin {\beta} and {\gamma} polymorphs has been studied by a combination of diffuse scattering, inelastic x-ray scattering and density functional perturbation theory. The non-symmorphic space group of the…

Probabilistic graphical models compactly represent joint distributions by decomposing them into factors over subsets of random variables. In Bayesian networks, the factors are conditional probability distributions. For many problems, common…

Machine Learning · Computer Science 2018-08-21 Weirui Kong , Wenyi Wang

We consider a one-parameter family of invertible maps of a two-dimensional lattice, obtained by applying round-off to planar rotations. All orbits of these maps are conjectured to be periodic. We let the angle of rotation approach pi/2, and…

Dynamical Systems · Mathematics 2014-06-02 Heather Reeve-Black

We present a new microscopic model of granular medium to study the role of dynamical correlations and the onset of spatial order induced by the inelasticity of the interactions. In spite of its simplicity, it features several different…

Statistical Mechanics · Physics 2009-11-07 A. Baldassarri , U. Marini Bettolo Marconi , A. Puglisi

The theory of deep inelastic scattering structure functions is reviewed with an emphasis put on the QCD expectations of their behaviour in the region of small values of the Bjorken parameter $x$.

High Energy Physics - Phenomenology · Physics 2007-05-23 J. Kwiecinski
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