Control of the spectrum of MeV electrons accelerated in laser plasma of nitrogen clusters
Control of the spectrum of MeV electrons accelerated in laser plasma of nitrogen clusters
A. A. Tausenev$^{1,2}$, P. A. Shcheglov$^1$, M. V. Chashchin$^1$, A. V. Lazarev$^3$, T. A. Semenov$^1$, M. M. Nazarov$^1$
The influence of the sizes of nitrogen clusters on the spectrum of MeV electrons accelerated in a cluster laser plasma under the influence of 5 TW femtosecond laser pulses has been studied. For this task, an electronic magnetic spectrometer was developed and created for the energy ranges: 0.3 – 5 MeV, or 1 – 10.5 MeV. The measured electronic spectra consist of a quasi-monoenergetic peak at 0.4±0.1 MeV, a broad “peak” at 2-3 MeV with an exponential tail with a temperature T = 3±1 MeV. It is shown that the maximum injection of electrons into the accelerating wave is achieved for clusters with an average radius corresponding to the Coulomb explosion limit. The electron bunch was the sum of collimated (10 mrad) and divergent (≈100 mrad) beams with maximum energies up to 10 MeV, which may indicate a hybrid acceleration mode.
Show AbstractСontrolling the spectral characteristics of terahertz radiation by means of multilayer dielectric structures
Сontrolling the spectral characteristics of terahertz radiation by means of multilayer dielectric structures
I. N. Nikolaeva$^{1,2,3}$, G. S. Rogozhnikov$^3$
Experimental research on interaction of mm-wavelength terahertz radiation with multilayer dielectric structures have been carried out. Possibilities of spatial and spectral characteristics control for practical use in secure communication, opaque vision and distant sounding have been shown.
Show AbstractIdentification and examination of protein compounds utilizing Raman scattering and machine learning techniques
Identification and examination of protein compounds utilizing Raman scattering and machine learning techniques
A. S. Shtumpf
Proteins are important components of the human body, playing a crucial role in the functioning of cells: they catalyze chemical reactions and form cellular structures. An imbalance in protein metabolism can have serious consequences, such as impaired immunity and changes in glandular activity. Detection of various biological compounds is challenging due to their complex intermolecular relationships, and traditional methods such as immunoassays and chromatography may not always provide accurate results. The presented research aims to overcome these limitations by introducing an approach that combines Raman spectroscopy and machine learning to accurately identify protein compounds. This technique aims to minimize errors in quantitative and qualitative analysis and enable systematic investigation of protein compounds.The results obtained during testing of the algorithm on data obtained during experiments indicate the possibility of using this technique for more than 10 analyte substances and achieving an accuracy of over 90%. The methodology for working with experimental data using artificial intelligence tools thus formed can form the basis for creating effective platforms and devices for use not only in the scientific field, but also in the fields of medicine, agriculture, and food safety.
Show AbstractInvestigation of prognostic anomalies of induced seismicity in the Koina and Varna reservoirs.
Investigation of prognostic anomalies of induced seismicity in the Koina and Varna reservoirs.
A. I. Polovnikova
Seismic activity is one of the most dangerous and unstable natural phenomena on our planet. Research in the field of seismology is of great importance for minimizing the risks associated with earthquakes and improving the quality of their forecast. Induced seismicity refers to earthquakes that are caused by human activity. An example of such activity is the construction and use of hydraulic structures, such as dams or reservoirs. During the preparation of strong earthquakes, the distribution of seismic events in the space-time domain and their energy spectrum changes. Such changes are called anomalies of the seismic regime, they can be detected by analyzing the parameters of seismicity, which indirectly describe the state of the geophysical environment. Despite its high fundamental and practical importance, few publications have been devoted to the analysis of predictive anomalies in induced seismicity. In this paper, the question of the presence or absence of anomalies of the seismic regime before earthquakes in the field of induced seismicity is considered. Studies are being conducted for strong earthquakes in the area of Koina and Varna reservoirs in India. Preliminary preparation of the catalog is carried out, control of the representative magnitude, calculation of spatial maps of seismicity parameters. The results obtained can be used to develop effective measures to reduce risks and ensure the safety of the population, and can also clarify some features of the earthquake preparation process in areas of induced seismicity.
Show AbstractUse of an assembly of two thermal conductometric sensors for detection of hydrogen emissions
Use of an assembly of two thermal conductometric sensors for detection of hydrogen emissions
A. E. Elyanov, V. M. Bocharnikov, V. V. Volodin, V. V. Golub, N. K. Dentsel
The work shows the possibility of using an assembly of two thermоconductometric sensors to simultaneously measure the flow speed of a gas mixture and the hydrogen content in it. A measurement concept has been proposed using one sensor located in the flow of the test gas, and a second one closed with a mesh cap, which reduces the dependence of the sensor readings on the flow speed. Test assemblies were manufactured and calibration experiments were carried out in the range of speeds from 0 to 1.84 m/s, hydrogen concentrations from 0 to 100 vol.% and absolute pressure from 0.1 to 5 atm. The results of calibration experiments show that from the signals from two sensors it is possible to unambiguously obtain the flow speed values and hydrogen content in the gas mixture at the location of the sensors. Formulas for converting signals into the required physical quantities are obtained. The assemblies are installed in a test container to study the mixing of hydrogen with air. The response time of the assembly to changes in hydrogen concentration does not exceed 1 s, which allows its use for signaling hydrogen emissions and studying the mixing of hydrogen with air. Graphs of the flow rate and concentration of hydrogen in the mixture versus time are presented.
Show AbstractRare decays of $D_s$ mesons into light pseudoscalar mesons
Rare decays of $D_s$ mesons into light pseudoscalar mesons
V. O. Galkin$^1$, I. S. Sukhanov$^{1,2}$
Rare decays of $D_s$ mesons into pseudoscalar mesons are studied in detail within the framework of the relativistic quark model based on the quasipotential approach and quantum chromodynamics. The form factors that parameterize the matrix elements of the weak current between meson states are calculated with consistent account of relativistic effects. Their dependence on the square of the transferred momentum is explicitly defined in the whole accessible kinematic region. The effects of electroweak physics at short distances and the contributions of intermediate resonances at large distances are taken into account using effective Wilson coefficients,. In the framework of the helicity formalism, differential decay rates and branching fraction are calculated. The obtained results are consistent with the existing upper experimental limits.
Show AbstractMathematical methods for analyzing the shape of time series and their applications to remote sensing of the Earth and atmosphere
Mathematical methods for analyzing the shape of time series and their applications to remote sensing of the Earth and atmosphere
A. F. Idrisov
The work is devoted to methods of time series analysis based on the theory of morphological analysis and measuring and computing systems developed at the Department of Mathematical Modeling and Computer Science of the Faculty of Physics of Lomonosov Moscow State University. Modern relevant methods of time series analysis have been studied. A morphological filtering method is proposed to detect a trend in a time series. A computer experiment was conducted on real experimental data (temperature measurements in the city of Tver) using the above method. The results demonstrated the successful identification of the trend component of the time series. It is planned to develop new methods of time series analysis to solve a wider class of problems for a wider class of input data.
Show AbstractUltra-high energy cosmic rays: sources, acceleration processes and GZK phenomena
Ultra-high energy cosmic rays: sources, acceleration processes and GZK phenomena
P. V. Alexandrovna$^1$, T. I. Yurievicn$^2$
Ultra-high energy cosmic rays (UHECR) reach an energy of 1020 eV, which is a million times higher than the energy achieved in artificial particle accelerators. The arrival of high-energy particles from space occurs infrequently, so detectors with a large area are required to register such events. It is necessary to understand what known effects can accelerate and decelerate particles to such energies. The upper energy limit is the Greisen-Zatsepin-Kuzmin (GZK) effect. This process significantly limits the possible distance to sources, and it should lead to suppression of the high-energy part of the spectrum. This work analyzes the GZK effect for nuclei from hydrogen to iron
Show AbstractDevelopment of a digital version of a space debris recognition system based on artificial intelligence
Development of a digital version of a space debris recognition system based on artificial intelligence
A. V. Shavshin$^1$, V. V. Davydov$^1$, D. A. Boldarev$^2$, R. A. Dmitriev$^1$, D. Yu. Klimenko$^2$, A. A. Hudina$^2$
The relevance of developing a space debris recognition system based on artificial intelligence is substantiated. A digital version of a space debris recognition system based on artificial intelligence has been developed, which can serve as the basis for creating a full-fledged system. The development of artificial intelligence code, its training and testing on experimental data was carried out. It has been established that the created digital version of the space debris recognition system based on artificial intelligence has the potential for successful detection and classification of space debris in the orbit of planet Earth.
Show AbstractEffect of partial unitarity requirements on the accuracy of measurements of Wilson coefficients in the processes of three and four top quarks production
Effect of partial unitarity requirements on the accuracy of measurements of Wilson coefficients in the processes of three and four top quarks production
A. M. Aleshko, E. E. Boos, V. E. Bunichev, L. V. Dudko
The problem of violation of unitarity in the Effective Field Theory of Standard Model (SMEFT) when applied to the processes of three and four top quarks production for relevant efficient operators. Using the optical theorem, boundaries of areas corresponding to the condition of non-violation of partial unitarity were determined. It was shown, how these restrictions affect the accuracy of setting limits on the corresponding Wilson coefficients. It has been established that for the processes under study, the influence of unitary restrictions is noticeable and leads to a deterioration in the accuracy of setting the corresponding limits even at collision energies of 13 and 14 TeV.
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