Related papers: Learning Hadron Emitting Sources with Deep Neural …
In this work, we present a study of particle production in proton-proton collisions using data that are collected from many experiments of relative wide range of reaction energies. These data include production of pions and heavier…
We discuss different sources of hadron correlations in relativistic heavy ion collisions. We show that correlations among partons in a quasi-thermal medium can lead to the correlated emission of hadrons by quark recombination and argue that…
Two-particle correlations play a pivotal role in understanding the space-time characteristics of particle emission in Heavy-ion collisions. These characteristics are typically represented by a relative emission source and can be obtained…
At the extreme energies of the Large Hadron Collider, massive particles can be produced at such high velocities that their hadronic decays are collimated and the resulting jets overlap. Deducing whether the substructure of an observed jet…
The momentum correlation functions of baryon pairs, which reflects the baryon-baryon interaction at low energies, are investigated for multi-strangeness pairs ($\Omega\Omega$ and $N\Omega$) produced in relativistic heavy-ion collisions. We…
We predict a strong enhancement of multijet production in proton-nucleus collisions at collider energies, as compared to a naive expectation of a cross section $\propto A$. The study of the process would allow to measure, for the first…
The diffusion coefficient of heavy quarks in the deconfined medium is examined in this research using a deep convolutional neural network (CNN) trained with data from relativistic heavy ion collisions involving heavy flavor hadrons. The CNN…
Proton-proton collision is a simple system to investigate nuclear matter and it is considered to be a guide for more sophisticated processes in the proton-nucleus and the nucleus-nucleus collisions. In this article, we present a…
The study of correlations among particles produced in different rapidity regions may provide understanding of the mechanisms of particle production. Correlations that extend over a longer range are observed in hadron-hadron interactions…
We develop a method for detecting the inhomogeneity of the pion-emitting sources produced in ultra-relativistic heavy ion collisions, through event-by-event two-pion Bose-Einstein correlations. The root-mean-square of the…
We will show an application of neural networks to extract information on the structure of hadrons. A Monte Carlo over experimental data is performed to correctly reproduce data errors and correlations. A neural network is then trained on…
Many--particle correlations due to Bose-Einstein interference are studied in ultrarelativistic heavy--ion collisions. We calculate the higher order correlation functions from the 2--particle correlation function by assuming that the source…
We make the connection between certain deep learning architectures and the renormalisation group explicit in the context of QCD by using a deep learning network to construct a toy parton shower model. The model aims to describe…
Studies of the ultrarelativistic collisions of hadrons and nuclei at different centrality and energy enable to explore the QCD phase diagram in a wide range of temperature and baryon density. Long-range correlation studies are considered as…
The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train…
Two-particle pseudorapidity correlations are analyzed in a simple model, where in the initial stage of the reaction multiple sources, extended in rapidity, are created. We show how the fluctuations of the length of the sources in rapidity…
Proton-proton correlations from spectator decays following Au + Au collisions at 1000 AMeV have been measured with an highly efficient detector hodoscope. The constructed correlation functions indicate a moderate expansion and low breakup…
We review some selected results of the tensor-pomeron and vector-odderon model of soft high-energy proton-proton scattering and central exclusive production of meson and baryon pairs in proton-proton collisions. We discuss the theoretical…
A method for reconstructing the direction of a fast neutron source using a segmented organic scintillator-based detector and deep learning model is proposed and analyzed. The model is based on recurrent neural network, which can be trained…
It is well understood that the studies of correlations between produced particles, the effects of coherence and chaoticity, an estimation of particle emitting source size play an important role in high energy physics [1]. First of all, we…