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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Influence of the Normal Magnetic Component to Magnetotail Current Sheet Forma

Cosmic Research. 2026. Vol. 64. No. 2. P. 238–252.
Domrin V. I., Malova H. V., V. Yu. Popov, Mingalev O. V., Kalegaev V. V., Grigorenko E. E., Zelenyi L. M.

During magnetospheric perturbations a relatively thin current sheet with thickness about several
proton gyroradii forms in the Earth’s magnetotail. In a framework of the kinetic model describing current
sheet thinning in the magnetotail, the processes of its formation are investigated depending on the normal
magnetic field magnitude which affects both the current sheet structure and particle dynamics within it. The
critical value of the ratio of the normal to tangential components magnitudes at current sheet edges is determined
above which the formation of a stationary thin current sheet does not occur. The reason for this is the
high density of trapped plasma particles around the sheet, which contribute to its magnetotail structure and
finally lead to its destruction. It is shown that this ratio can be the important factor influencing quasi-equilibrium
state of magnetotail current sheet as a whole and determining the characteristic parameter range at
which the formation of a long-lived current structure with small thickness is possible.

Research target: Computer Science Mathematics Physics
Language: English
Full text
DOI
Keywords: magnetosphereMagnetotailcurrent sheet modelingquasi-adiabatic particle dynamics
Publication based on the results of:
Complex language and semantic models in artificial intelligence (2025)
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