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  • ИСТОРИЯ И ПЕРСПЕКТИВЫ АТОМИСТИЧЕСКОГО МОДЕЛИРОВАНИЯ ПОЛИСАХАРИДОВ
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News
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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ИСТОРИЯ И ПЕРСПЕКТИВЫ АТОМИСТИЧЕСКОГО МОДЕЛИРОВАНИЯ ПОЛИСАХАРИДОВ

Высокомолекулярные соединения. Серия С. 2023. Т. 65. № 1. С. 91–109.
Дещеня В. И., Kondratyuk N.

The history and prospects for the development of interatomic interaction potentials for the simulation of molecular systems and, in particular, polysaccharides are presented. Popular families of potentials, such as CHARMM, GROMOS, AMBER, and OPLS, are considered. Problems that limit the applicability of these models to sugar monomers have been recognized, which are poor reproducibility of experimentally determined properties and hyperaggregation at low concentrations. The development vectors of this area are also considered: the modification of nonbonded interactions and the use of polarizable potentials. Applications of the atomistic simulation of polysaccharides in actual fundamental and industrial problems are demonstrated using the example of cellulose. Important computational works are presented that have made a significant contribution to the understanding of the structure and processes occurring in a cellulose crystal. In addition, an overview is given of the currently available time scales and characteristic sizes of systems for simulation in the GROMACS, LAMMPS, OpenMM, and AMBER packages for the sucrose solution model.

Research target: Physics Computer Science
Language: Russian
DOI
Text on another site
Keywords: потенциал взаимодействия частицвязкостьклассическая молекулярная динамикаполисахариды
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