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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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Magnetohydrodynamic Modeling of the Solar Wind Key Parameters and Current Sheets in the Heliosphere: Radial and Solar Cycle Evolution

Astrophysical Journal. 2020. Vol. 892. No. 1. P. 1–17.
E. V. Maiewski, Kislov R. A., Khabarova O. V., Malova H. V., V. Yu. Popov, Petrukovich A. A., Zelenyi L. M.

We develop an axisymmetric numerical MHD model that allows us to investigate the spatial characteristics of the interplanetary magnetic field (IMF) and key solar wind plasma parameters from 20 to 400 solar radii over all heliolatitudes. The study is aimed at an analysis of the evolution of the spatial structure of the heliosphere through the solar cycle. We consider various combinations of the relative input of the quadrupole and dipole harmonics of the solar magnetic field to imitate the solar cycle. Self-consistent solutions for the IMF, electric current, solar wind speed, density, thermal pressure, and temperature in the solar wind are obtained. The spatial evolution of the IMF and properties of quasi-stationary current sheets (QCSs) are analyzed during different phases of the solar cycle. It is shown that a classic low-latitude heliospheric current sheet is formed in the solar wind as a part of the system of longitudinal and latitudinal electric currents symmetric in the northern and southern hemispheres only during solar minimum. While the quadrupole magnetic field increases, the second QCS appears. The model successfully describes a smooth transition from the state of the fast solar wind at high heliolatitudes and the slow solar wind at low heliolatitudes at solar minimum to the solar wind speed of the same values in a wide range of heliolatitudes at solar maximum. It reproduces the actively debated phenomenon of the south–north asymmetry of the IMF in the heliosphere and shows the distribution of thermal plasma parameters consistent with observations.

Research target: Physics
Priority areas: IT and mathematics
Language: English
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Keywords: solar wind magnetohydrodynamicsheliospheresolar activitySolar magnetic fields
Publication based on the results of:
Construction of mathematical models designed for the analysis of data series, prediction of big systems’ evolution, and the control of the dynamics of these systems (2019)
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