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AbstractThe semi-classical approach to the calculating electromagnetic fields formed by interaction between hard radiation and matter is used to consider the passage of high-energy positrons through a gas medium. Results from calculating changes in electromagnetic fields in the optical range for air when high-energy positrons pass through it are presented.

AbstractCalculations are made for the angular distributions of changes in the energy of an electromagnetic field in the optical range formed by the interaction between high-energy electrons and a gas medium. The calculated values ​​of the angular distributions are consistent with ones observed experimentally.

AbstractIn our work we investigated the application of artificial neural networks (ANNs) to event-wise analysis of heavy ion collision data. We focused on solving the problem of impact parameter estimation using simulated data from a microchannel plate detector (MCP) for potential use in NICA (Nuclotron-based Ion Collider fAcility) collider experiments. Our study reveals that such a technique can be utilized to estimate the impact parameter quite accurately from raw detector data based on the QGSM event generator, specifically from spatial distributions of particles and time-of-flight distributions. However, ANNs results are highly dependent on the model of event generator used to create the dataset. Repeating the experiments with data from an alternative generator based on the EPOS collision model yielded different results. Despite this model dependence of the ANNs, we discuss the way they can be used for extraction of model-independent information. Moreover, we have shown that the detector parameters providing the best reconstruction of the event parameters do not depend on the Monte Carlo model of the event and, therefore, are more likely to be optimal in future collider experiments.

AbstractA way of calculating the angular distribution of changes in the energy of optical radiation generated by high-energy electrons passing through a solid transparent body is proposed that allows for the contribution from secondary electrons. The values are found of the angles at which peaks in optical radiation are observed when electrons pass through mica and glass.

The results of studying the flow structure and the concentrations of toxic substances in the primary zone of a combustion chamber with a two-tier arrangement of injectors operating on kerosene are reported. The design features of injectors installed in the front device of the combustion chamber are given. The bench equipment and the combustion chamber section used in the study are described.

We study one-dimensional flows of an ideal (inviscid and non-heat-conducting) perfect gas with an adiabatic exponent γ behind a shock wave moving toward the center (ν = 3) or axis (ν = 2) of symmetry in a cold gas at rest. Flows with a reflected shock wave and flows terminating with simultaneous arrival of a shock wave and a piston, which has compressed the gas into a point or line, to the center of symmetry are admitted.

Evaluation of the impact parameter in a single event of relativistic heavy ion collision is crucial for correct and efficient data processing and analysis. In this work we have studied the possibility of estimating the impact parameter in heavy ion collisions by using artificial neural networks applied to the charged particle data from fast microchannel plate (MCP) detectors. Charged particles’ multiplicity, their spatial distribution and time-of-flight data were used as event features to be analyzed by the artificial neural network algorithms. We investigated two different configurations of microchannel plate detector layout, that have different data and computational requirements. We have shown that the developed artificial neural networks technique is capable of providing sufficiently good and fast results on the impact parameter determination in a single heavy ion collision event for both configurations of MCP detectors layout. In our first exercises, the proposed algorithm has successfully identified more than 90 of Au Au collision events with the impact parameter less than 5 fm or less than 1 fm, which suggests its use as a fast trigger.

The problem of determining the coordinates of Au–Au interactions at a center-of-mass energy of 7 GeV and the influence of different ion beam pipe configurations on the results are considered. The modeling was performed using the UrQMD 3.4 event generator, Geant4, and a neural network model. Eight configurations were studied: ion beam pipes with wall thicknesses of 1.2, 3, 5, and 8 mm, with the wall material being carbon and iron. The use of beam pipe with walls with thicknesses of 1–3 mm does not significantly affect the outcome, but further increasing the wall thickness significantly reduces accuracy.

The paper describes the test bench equipment and the results of a study on the content of toxic substances in the combustion products of a turbulent flame of a homogeneous kerosene-air mixture as well as in the combustion products at the outlet of different variants of burner devices. The content of toxic substances is presented as a function of the excess air coefficient. A burner device with toxic substance content close to the values obtained during combustion of a homogeneous kerosene-air mixture was chosen.

This Erratum replaces, due to a discovery of coding mistakes, the following quantities: κ3/κ1 of the h+ − h− distribution presented in Fig. 6 and Table 6, κ4 listed in Table 4, and Ĉ4 presented in Fig. 7 and Table 5. All mentioned figures and tables were updated.