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In the framework of the relativistic quantum dynamics approach we investigate antiproton observables in Au-Au collisions at 10.7A GeV. The rapidity dependence of the in-plane directed transverse momentum p(y) of p's shows the opposite sigh of the nucleon flow, which has indeed recently been discovered at 10.7A GeV by the E877 group. The "antiflow" of p's is also predicted at 2A GeV and at 160 A GeV and appears at all energies also for pi's and K's. These predicted p anticorrelations are a direct proof of strong p annihilation in massive heavy ion reactions.
A new method of event characterization based on Deep Learning is presented. The PointNet models can be used for fast, online event-by-event impact parameter determination at the CBM experiment. For this study, UrQMD and the CBM detector simulation are used to generate Au+Au collision events at 10 AGeV which are then used to train and evaluate PointNet based architectures. The models can be trained on features like the hit position of particles in the CBM detector planes, tracks reconstructed from the hits or combinations thereof. The Deep Learning models reconstruct impact parameters from 2-14 fm with a mean error varying from -0.33 to 0.22 fm. For impact parameters in the range of 5-14 fm, a model which uses the combination of hit and track information of particles has a relative precision of 4-9% and a mean error of -0.33 to 0.13 fm. In the same range of impact parameters, a model with only track information has a relative precision of 4-10% and a mean error of -0.18 to 0.22 fm. This new method of event-classification is shown to be more accurate and less model dependent than conventional methods and can utilize the performance boost of modern GPU processor units.
The coordinate and momentum space configurations of the net baryon number in heavy ion collisions that undergo spinodal decomposition, due to a first-order phase transition, are investigated using state-of-the-art machine-learning methods. Coordinate space clumping, which appears in the spinodal decomposition, leaves strong characteristic imprints on the spatial net density distribution in nearly every event which can be detected by modern machine learning techniques. On the other hand, the corresponding features in the momentum distributions cannot clearly be detected, by the same machine learning methods, in individual events. Only a small subset of events can be systematically differ- entiated if only the momentum space information is available. This is due to the strong similarity of the two event classes, with and without spinodal decomposition. In such sce- narios, conventional event-averaged observables like the baryon number cumulants signal a spinodal non-equilibrium phase transition. Indeed the third-order cumulant, the skewness, does exhibit a peak at the beam energy (Elab = 3–4 A GeV), where the transient hot and dense system created in the heavy ion collision reaches the first-order phase transition.
The thermal fit to preliminary HADES data of Au+Au collisions at sNN=2.4 GeV shows two degenerate solutions at T≈50 MeV and T≈70 MeV. The analysis of the same particle yields in a transport simulation of the UrQMD model yields the same features, i.e. two distinct temperatures for the chemical freeze-out. While both solutions yield the same number of hadrons after resonance decays, the feeddown contribution is very different for both cases. This highlights that two systems with different chemical composition can yield the same multiplicities after resonance decays. The nature of these two minima is further investigated by studying the time-dependent particle yields and extracted thermodynamic properties of the UrQMD model. It is confirmed, that the evolution of the high temperature solution resembles cooling and expansion of a hot and dense fireball. The low temperature solution displays an unphysical evolution: heating and compression of matter with a decrease of entropy. These results imply that the thermal model analysis of systems produced in low energy nuclear collisions is ambiguous but can be interpreted by taking also the time evolution and resonance contributions into account.
A novel method for identifying the nature of QCD transitions in heavy-ion collision experiments is introduced. PointNet based Deep Learning (DL) models are developed to classify the equation of state (EoS) that drives the hydrodynamic evolution of the system created in Au-Au collisions at 10 AGeV. The DL models were trained and evaluated in different hypothetical experimental situations. A decreased performance is observed when more realistic experimental effects (acceptance cuts and decreased resolutions) are taken into account. It is shown that the performance can be improved by combining multiple events to make predictions. The PointNet based models trained on the reconstructed tracks of charged particles from the CBM detector simulation discriminate a crossover transition from a first order phase transition with an accuracy of up to 99.8%. The models were subjected to several tests to evaluate the dependence of its performance on the centrality of the collisions and physical parameters of fluid dynamic simulations. The models are shown to work in a broad range of centralities (b=0–7 fm). However, the performance is found to improve for central collisions (b=0–3 fm). There is a drop in the performance when the model parameters lead to reduced duration of the fluid dynamic evolution or when less fraction of the medium undergoes the transition. These effects are due to the limitations of the underlying physics and the DL models are shown to be superior in its discrimination performance in comparison to conventional mean observables.
A primordial state of matter consisting of free quarks and gluons that existed in the early universe a few microseconds after the Big Bang is also expected to form in high-energy heavy-ion collisions. Determining the equation of state (EoS) of such a primordial matter is the ultimate goal of high-energy heavy-ion experiments. Here we use supervised learning with a deep convolutional neural network to identify the EoS employed in the relativistic hydrodynamic simulations of heavy ion collisions. High-level correlations of particle spectra in transverse momentum and azimuthal angle learned by the network act as an effective EoS-meter in deciphering the nature of the phase transition in quantum chromodynamics. Such EoS-meter is model-independent and insensitive to other simulation inputs including the initial conditions for hydrodynamic simulations.
Relying on the existing estimates for the production cross sections of mini black holes in models with large extra dimensions, we review strategies for identifying those objects at collider experiments. We further consider a possible stable final state of such black holes and discuss their characteristic signatures. Keywords: Black holes
We present a calculation of antiproton yields in Si+Al and Si+Au collisions at 14.5A GeV in the framework of the relativistic quantum molecular dynamics approach (RQMD). Multistep processes lead to the formation of high-mass flux tubes. Their decay dominates the initial antibaryon yield. However, the subsequent annihilation in the surrounding baryon-rich matter suppresses the antiproton yield considerably: Two-thirds of all antibaryons are annihilated even for the light Si+Al system. Comparisons with preliminary data of the E802 experiment support this analysis.
One of important consequences of Hagedorn statistical bootstrap model is the prediction of limiting temperature Tcrit for hadron systems colloquially known as Hagedorn temperature. According to Hagedorn, this effect should be observed in hadron spectra obtained in infinite equilibrated nuclear matter rather than in relativistic heavy-ion collisions. We present results of microscopic model calculations for the infinite nuclear matter, simulated by a box with periodic boundary conditions. The limiting temperature indeed appears in the model calculations. Its origin is traced to strings and many-body decays of resonances.
Dilepton spectra for p+p and p+d reactions at 4.9GeV are calculated. We consider electromagnetic bremsstrahlung also in inelastic reactions. N* and Delta* decay present the major contributions to the pho and omega meson yields.Pion annihilation yields only 1.5% of all pho's in p+d. The pho mass spectrum is strongly distorted due to phase space effects, populating dominantly dilepton masses below 770MeV.
The amount of proton stopping in central Pb+Pb collisions from 20–160 A GeV as well as hyperon and antihyperon rapidity distributions are calculated within the UrQMD model in comparison to experimental data at 40, 80, and 160 A GeV taken recently from the NA49 collaboration. Furthermore, the amount of baryon stopping at 160A GeV for Pb+Pb collisions is studied as a function of centrality in comparison to the NA49 data. We find that the strange baryon yield is reasonably described for central collisions, however, the rapidity distributions are somewhat more narrow than the data. Moreover, the experimental antihyperon rapidity distributions at 40, 80, and 160 A GeV are underestimated by up to factors of 3—depending on the annihilation cross section employed—which might be addressed to missing multimeson fusion channels in the UrQMD model. Pacs-Nr.: 25.75.2q, 24.10.Jv, 24.10.Lx
Strong mean meson fields, which are known to exist in normal nuclei, experience a violent deformation in the course of a heavy-ion collision at relativistic energies. This may give rise to a new collective mechanism of the particle production, not reducible to the superposition of elementary nucleon-nucleon collisions.
Recent calculations applying statistical mechanics indicate that in a setting with compactified large extra dimensions a black hole might evolve into a (quasi-)stable state with mass close to the new fundamental scale Mf. Black holes and therefore their relics might be produced at the LHC in the case of extra-dimensional topologies. In this energy regime, Hawking's evaporation scenario is modified due to energy conservation and quantum effects. We reanalyse the evaporation of small black holes including the quantisation of the emitted radiation due to the finite surface of the black hole. It is found that observable stable black hole relics with masses ∼1–3Mf would form which could be identified by a delayed single jet with a corresponding hard momentum kick to the relic and by ionisation, e.g., in a TPC.
We demonstrate the importance of the Bose-statistical effects for pion production in relativistic heavy-ion collisions. The evolution of the pion phase-space density in central collisions of ultrarelativistic nuclei is studied in a simple kinetic model taking into account the effect of Bose-simulated pion production by the NN collisions in a dense cloud of mesons.
We study the bound states of anti-nucleons emerging from the lower continuum in finite nuclei within the relativistic Hartree approach including the contributions of the Dirac sea to the source terms of the meson fields. The Dirac equation is reduced to two Schr¨odinger-equivalent equations for the nucleon and the anti-nucleon respectively. These two equations are solved simultaneously in an iteration procedure. Numerical results show that the bound levels of anti-nucleons vary drastically when the vacuum contributions are taken into account. PACS number(s): 21.10.-k; 21.60.-n; 03.65.Pm
We study properties of compact stars with the deconfinement phase transition in their interiors. The equation of state of cold baryon-rich matter is constructed by combining a relativistic mean-field model for the hadronic phase and the MIT Bag model for the deconfined phase. In a narrow parameter range two sequences of compact stars (twin stars), which differ by the size of the quark core, have been found. We demonstrate the possibility of a rapid transition between the twin stars with the energy release of about 1052 ergs. This transition should be accompanied by the prompt neutrino burst and the delayed gamma-ray burst.
The interplay of charmonium production and suppression in In+In and Pb+Pb reactions at 158 AGeV and in Au+Au reactions at sqrt(s)=200 GeV is investigated with the HSD transport approach within the hadronic comover model' and the QGP melting scenario'. The results for the J/Psi suppression and the Psi' to J/Psi ratio are compared to the recent data of the NA50, NA60, and PHENIX Collaborations. We find that, at 158 AGeV, the comover absorption model performs better than the scenario of abrupt threshold melting. However, neither interaction with hadrons alone nor simple color screening satisfactory describes the data at sqrt(s)=200 GeV. A deconfined phase is clearly reached at RHIC, but a theory having the relevant degrees of freedom in this regime (strongly interacting quarks/gluons) is needed to study its transport properties.
The state-of-the-art pattern recognition method in machine learning (deep convolution neural network) is used to identify the equation of state (EoS) employed in the relativistic hydrodynamic simulations of heavy ion collisions. High-level correlations of particle spectra in transverse momentum and azimuthal angle learned by the network act as an effective EoS-meter in deciphering the nature of the phase transition in QCD. The EoS-meter is model independent and insensitive to other simulation inputs including the initial conditions and shear viscosity for hydrodynamic simulations. Through this study we demonstrate that there is a traceable encoder of the dynamical information from the phase structure that survives the evolution and exists in the final snapshot of heavy ion collisions and one can exclusively and effectively decode these information from the highly complex final output with machine learning when traditional methods fail. Besides the deep neural network, the performance of traditional machine learning classifiers are also provided.