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Information × Registration Number 0224U003094, 0123U102998 , R & D reports Title Modeling systems of strongly interacting and dark matter popup.stage_title Head Rudakovskyi Anton V., Кандидат фізико-математичних наук Registration Date 06-04-2024 Organization М.М.Bogolyubov Institute of Theoretical Physics of the National Academy of Sciences of Ukraine popup.description2 The object of research is the Early Universe, dark matter, quark-gluon plasma, and nuclear-nuclear collisions. The purpose of this topic was the study of dark matter, the search for its manifestations in cosmology, as well as the search for the critical behavior of strongly interacting matter, and the simulation of collider experiments. Neural networks (specifically moment neural networks) were tested for estimating cosmological parameters using cosmological simulations from the CAMELS project. It was found that the estimation of these parameters is consistent with the real values used in the simulations. The results demonstrate that a physically based parameterization can overcome strong degeneracy between posterior parameter values. The network trained on SIMBA simulations correctly (within 1 sigma errors) estimates the cosmological parameters from the IllustrousTNG simulations, despite differences in the physical models of galaxy formation. The global absorption signal at a wavelength of 21 cm was simulated using the ARES code, taking into account the influence of stars from the third stellar population. The integrated hydro-kinetic model has been modified. A computer code was developed in the C++ language that calculates the energy-momentum tensor of a non-equilibrium hadronic gas at a constant eigentime in Milne coordinates. This code was integrated into the main model using Bash and Python scripts. The result was used to calculate the initial conditions for the relaxation stage of nuclear-nuclear collisions at GeV energies within the framework of the model. Product Description popup.authors Adzhimambetov Musfer D. Rudakovskyi Anton V. popup.nrat_date 2024-04-06 Close