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We report on the low and moderate Q^2 nucleon spin structure measurements done at Jefferson Lab, examining specifically the inclusive program. We discuss what the data teach us about quark confinement and the emergence of the effective…
MLPACK is a state-of-the-art, scalable, multi-platform C++ machine learning library released in late 2011 offering both a simple, consistent API accessible to novice users and high performance and flexibility to expert users by leveraging…
Modelling of multivariate densities is a core component in many signal processing, pattern recognition and machine learning applications. The modelling is often done via Gaussian mixture models (GMMs), which use computationally expensive…
In the first part, I give a brief description of the quark-gluon plasma search at CERN and of some experimental results. In the second part, I review a dynamical model of nucleus-nucleus interactions and propose a physical interpretation of…
In this paper we describe the implementation of our C++ resistive magnetohydrodynamics solver. The framework developed facilitates the separation of the code implementing the specific numerical method and the physical model, on the one…
We investigate dijet production from proton-nucleus collisions at the Large Hadron Collider (LHC) as a means for observing superfast quarks in nuclei with Bjorken $x>1$. Kinematically, superfast quarks can be identified through directly…
The evolution of matter produced in nucleus collisions is investigated in the frame work of the simplified fluid equation, where the compressible bag model is used as the equation of state for hadrons. It is shown that the quark-gluon phase…
The paper gives an overview of the principles of particle accelerators and their historical development. After introducing the basic concepts, the main emphasis is on sketching the layout of modern storage rings and discussing their…
This article presents a comparison of various implementations of the Lattice Discrete Particle Model (LDPM) for the numerical simulation of concrete and other heterogeneous quasibrittle materials. The comparison involves the use of…
The form of the kernel that controls the dynamics of the Bethe-Salpeter equations is essential for obtaining quantitatively accurate predictions for the observable properties of hadrons. In the present work we briefly review the basic…
The physics of high-energy collider experiments asks for delicate comparisons between theoretical predictions and experimental data. Signals and potential backgrounds for new physics have to be predicted at sufficient accuracy. The accuracy…
We present qcor - a language extension to C++ and compiler implementation that enables heterogeneous quantum-classical programming, compilation, and execution in a single-source context. Our work provides a first-of-its-kind C++ compiler…
In the Color Glass Condensate(CGC) effective theory, the physics of valence gluons with large longitudinal momentum is reflected in the distribution of color charges in the transverse plane. Averaging over the valence degrees of freedom is…
Lattice simulations of hadronic structure are now reaching a level where they are able to not only complement, but also provide guidance to current and forthcoming experimental programmes at, e.g. Jefferson Lab, COMPASS/CERN and FAIR/GSI.…
The rapidity dependence of the initial energy density in heavy-ion collisions is calculated from a three-dimensional McLerran-Venugopalan model (3dMVn) introduced by Lam and Mahlon. This model is infrared safe since global color neutrality…
We present a short overview of saturation physics followed by a summary of the recent progress in our understanding of nonlinear small-$x$ evolution. Topics include McLerran-Venugopalan model, Glauber-Mueller approximation, nonlinear…
A hadron collider operating at an energy much larger than the LHC ("HE-LHC") would be a logical successor to the LHC itself, especially if its cost can be minimized by reusing a significant part of the CERN infrastructure like the existing…
The irradiation represents a useful tool for determining the characteristics of defects in semiconductors as well as a method to evaluate their degradation, fact with important technological consequences. In this contribution, starting from…
To address increasing compute demand from recent multi-model workloads with heavy models like large language models, we propose to deploy heterogeneous chiplet-based multi-chip module (MCM)-based accelerators. We develop an advanced…
As the usage of deep learning becomes increasingly popular in mobile and embedded solutions, it is necessary to convert the framework-specific network representations into executable code for these embedded platforms. This paper consists of…