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Basic problems of the semiclassical microscopic modelling of strongly interactingsystems are discussed within the framework of Quantum Molecular Dynamics (QMD). This model allows to study the influence of several types of nucleonic…

Nuclear Theory · Physics 2014-11-18 C. Hartnack , Rajeev K. Puri , J. Aichelin , J. Konopka , S. A. Bass , H. Stoecker , W. Greiner

The complex nature of inertial confinement fusion (ICF) experiments results in a very large number of experimental parameters that are only known with limited reliability. These parameters, combined with the myriad physical models that…

Plasma Physics · Physics 2015-06-15 Jim A Gaffney , Dan Clark , Vijay Sonnad , Stephen B Libby

This article summarizes our present knowledge about nuclear matter at the highest energy densities and its formation in relativistic heavy ion collisions. We review what is known about the structure and properties of the quark-gluon plasma…

Nuclear Theory · Physics 2022-10-24 Hannah Elfner , Berndt Müller

We study the phenomenon of jet quenching utilizing quark and gluon jet substructures as independent probes of heavy ion collisions. We exploit jet and subjet features to highlight differences between quark and gluon jets in vacuum and in a…

High Energy Physics - Phenomenology · Physics 2018-03-12 Yang-Ting Chien , Raghav Kunnawalkam Elayavalli

Energy correlators have recently been proposed as a class of jet substructure observables that directly link experimental measurements of the asymptotic energy flux with the field theoretic description of the underlying microscopic…

High Energy Physics - Phenomenology · Physics 2024-09-18 Carlota Andres , Fabio Dominguez , Jack Holguin , Cyrille Marquet , Ian Moult

The application of quark models to the spectra and strong and electromagnetic couplings of baryons is reviewed. This review focuses on calculations which attempt a global description of the masses and decay properties of baryons, although…

Nuclear Theory · Physics 2008-11-26 Simon Capstick , W. Roberts

Combining predictions from different models is a central problem in Bayesian inference and machine learning more broadly. Currently, these predictive distributions are almost exclusively combined using linear mixtures such as Bayesian model…

Machine Learning · Statistics 2023-05-15 Yuling Yao , Luiz Max Carvalho , Diego Mesquita , Yann McLatchie

Jets are extended multipartonic systems and serve as a powerful tool for investigating the dynamics of emergent phenomena driven by many body QCD interactions. In heavy ion collisions, starting from their production during the perturbative…

High Energy Physics - Phenomenology · Physics 2025-05-26 Balbeer Singh

We analyze the possibilities for studying properties of dense QCD-matter, created in ultrarelativistic nuclear collisions, by hard QCD-production processes, so-called "hard" probes -- heavy quarkonia, hard jets, high mass dimuons. Special…

High Energy Physics - Phenomenology · Physics 2016-09-06 I. P. Lokhtin

Nanopore sensors detect the substructure of individual molecules from modulations in an ion current as molecules pass through them. In this work, we present the classification of features in the substructure as a case study to illustrate…

Biological Physics · Physics 2019-04-03 Niklas Ermann , Kaikai Chen , Ulrich F. Keyser

Heavy-ion collisions are well described by a dynamical evolution with a long hydrodynamical phase. In this phase the properties of the strongly coupled quark-gluon plasma are reflected in the equation of state (EoS) and the transport…

Nuclear Theory · Physics 2018-12-06 A. Dubla , S. Masciocchi , J. M. Pawlowski , B. Schenke , C. Shen , J. Stachel

Bayesian inference provides a rigorous framework to encapsulate our knowledge and uncertainty regarding various physical quantities in a well-defined and self-contained manner. Utilising modern tools, such Bayesian models can be constructed…

High Energy Physics - Lattice · Physics 2024-01-02 Julien Frison

High-precision measurements require optimal setups and analysis tools to achieve continuous improvements. Systematic corrections need to be modeled with high accuracy and known uncertainty to reconstruct underlying physical phenomena. To…

Data Analysis, Statistics and Probability · Physics 2022-05-31 Max Lamparth , Mattis Bestehorn , Bastian Märkisch

Bayesian field theory denotes a nonparametric Bayesian approach for learning functions from observational data. Based on the principles of Bayesian statistics, a particular Bayesian field theory is defined by combining two models: a…

Data Analysis, Statistics and Probability · Physics 2007-05-23 J. C. Lemm

Fitting a simplifying model with several parameters to real data of complex objects is a highly nontrivial task, but enables the possibility to get insights into the objects physics. Here, we present a method to infer the parameters of the…

Data Analysis, Statistics and Probability · Physics 2018-12-21 Johannes Oberpriller , T. A. Enßlin

Nuclear collisions at intermediate, relativistic, and ultra-relativistic energies offer unique opportunities to study in detail manifold fragmentation and clustering phenomena in dense nuclear matter. At intermediate energies, the well…

Nuclear Theory · Physics 2007-05-23 Stefan Scherer , Horst Stocker

Quarks and gluons are the fundamental constituents of nucleons. Their interactions rather than their mass, is responsible for $99\%$ of the mass of all visible matter in the universe. Measuring the fundamental properties of matter has had a…

Nuclear Experiment · Physics 2019-05-06 Astrid Morreale

To reconstruct the impact parameter distributions from the selected events sample or centrality, which is defined by two-observables, at intermediate energy heavy ion collisions, we extend the approach proposed by Das \textit{et al.} [Phys.…

Nuclear Theory · Physics 2023-09-06 Xiang Chen , Li Li , Ying Cui , Junping Yang , Zhuxia Li , Yingxun Zhang

Bayesian analyses in the context of relativistic heavy-ion collisions have so far relied almost exclusively on bulk hadronic observables constructed from momentum degrees of freedom to constrain the transport properties of the quark-gluon…

Nuclear Theory · Physics 2026-05-29 Sushant K. Singh , Eduardo Grossi , Francesco Becattini

Bayesian methods are used to constrain the density dependence of the QCD Equation of State (EoS) for dense nuclear matter using the data of mean transverse kinetic energy and elliptic flow of protons from heavy ion collisions (HIC), in the…

High Energy Physics - Phenomenology · Physics 2023-11-20 Manjunath Omana Kuttan , Jan Steinheimer , Kai Zhou , Horst Stoecker
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