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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.
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‘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.
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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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Superconducting Spin Valves Based on a Single Spiral Magnetic Layer

Physical Review Applied. 2022. Vol. 18. No. 5. Article 054002.
Pugach N., Safonchik M. O., Belotelov V., Ziman T., Champel T.

A detailed investigation of a superconducting spin-triplet valve is presented. This spin valve consists of a superconducting film covering a metal with an intrinsic spiral magnetic order, which could result from competing isotropic exchanges or, if the crystal lattice breaks central symmetry, from asymmetric Dzyaloshinskii-Moriya exchange. Depending on the anisotropy, such a metal may change its magnetization either from a spiral to uniform order, as seen in Ho and Er, or in the direction of the spiral itself, as in crystals of the B20-type structure [such as MnSi, (Fe,Co)Si, FeGe, etc.]. The nonuniform magnetic order controls the appearance of long-range triplet superconducting correlations at strong exchange fields, affecting the detailed character of the proximity effect. We show that the magnetic control of the spin-valve behavior can also be obtained from moderately low exchange fields (typically associated to negligible long-range triplet correlations), thanks to an orientation-dependent averaging mechanism of the magnetic inhomogeneity on the scale of the Cooper pairs. Our numerical calculations reveal that the spin-valve effect is in fact magnified at moderately low exchange fields, when the exchange splitting in the spiral magnet is comparable to the superconducting gap, and the spiral period is less than or equal to the superconducting coherence length in the magnet multiplied by 2π.

Research target: Electronics and Electrical Engineering Nanotechnologies Physics
Language: English
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Keywords: спинтроникамагнетизмmagnetismspintronicsСверхпроводящие спиновые вентилисверхпроводящая спинтроника superconducting spintronicssuperconducting spin valves
Publication based on the results of:
Experimental and theoretical studies of quantum effects in low-dimensional systems (2022)
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