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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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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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Квантовый размерный эффект в сверхпроводниках

Известия Уфимского научного центра РАН. 2021. № 1. С. 39–43.
Sedov E., Zavyalov V., Arutyunov K.

In the middle of the last century, it was demonstrated that with a decrease in the size of superconducting structures, for example, the thickness of a thin film, its critical temperature TC shifts by a certain amount. It increases in aluminum, tin, and indium, and decreases in mercury, niobium, and lead. However, there is still no generally accepted theory explaining this effect. In the 1970s, during the largest volume of research on this topic, V.L. Ginzburg assumed that the transition temperature of a sufficiently pure, monocrystalline superconductor film will be exactly the same as in a bulk body. However, this assumption has not yet been verified, and the question  about the nature of this effect still remains open. For the study, we chose aluminum, due to the fact that the dependence of TC of the film on its thickness is very predictable and increases with decreasing size. Despite a number of works on studying this dependence in aluminum, it is not always possible to accurately establish a correspondence with a theory. This is because characteristics vary from sample to sample, even made in the same batch. In our case, polycrystalline films were prepared, the crystallite sizes in which are comparable to the film thickness, and epitaxial samples with an atomically smooth surface. The films were fabricated using electron-beam deposition and molecular-beam epitaxy on various substrates. Within the BCS model, the critical temperature of the superconducting transition exponentially depends on the density of electronic states at the Fermi level N(EF) and the electron-phonon interaction constant V: TC ~ exp(–1/[N(EF )*V]). It is shown in this work that, due to QSE in thin superconducting films, both parameters N(E F ) and V change nonmonotonically with the sample thickness. This behaviour is a consequence of the form resonance theory. Presumably, the effect caused by disordering of crystallites, as well as by the surface or substrate, does not play a dominant role specifically in our case, since the aluminum films are of high quality, and their thicknesses go far beyond the limits of ultrathin objects, in which surface phenomena become of decisive importance. As a result of this study, the experimental and theoretical dependences of TC on the thickness of films prepared by different methods on different substrates were obtained.

Research target: Physics
Priority areas: engineering science
Language: Russian
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Keywords: superconductivityсверхпроводимостьsapphire substrateсапфировая подложкаquantum size effectsквантовый размерный эффектmolecular-beam epitaxygallium arsenideМолекулярно-лучевая эпитаксияГаллий арсенид
Publication based on the results of:
Квантовые эффекты в низкоразмерных гибридных наноструктурах (2022)
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