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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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Reversible hydrogen storage in multilayer graphane: lattice dynamics, compressibility, and heat capacity studies

Materials Chemistry and Physics. 2025. Vol. 332. Article 130232.
Vladimir E. Antonov

Multilayer graphane (hydride of graphite) is a crystalline hydrocarbon of composition CH, which can be synthesized
from graphite and molecular hydrogen at pressures above 2 GPa [V.E. Antonov et al. Carbon 100 (2016)
465]. Using X-ray diffraction, this compound was tentatively identified as the “graphane II” phase of 3D-graphane
predicted by ab initio calculations [X.-D. Wen et al. PNAS 108 (2011) 6833] and consisting of layers of 2D-graphane in the “chair” conformation. When heated in a vacuum, the compound does not form any intermediate hydrocarbons and reversibly decomposes back into graphite and hydrogen at 770–920 K. In the present work, almost single-phase samples of graphite hydride and deuteride were synthesized at 7.4 GPa and 870 K. Their investigation by inelastic neutron scattering supplemented by ab initio calculations gave spectra g(E) of the phonon density of states with a gap of about 15 meV at approx. 100 meV, which is a unique identifier for the chair form of graphane. The equation of state V(P) of the hydride was studied at room temperature and hydrogen pressures up to 53 GPa by synchrotron X-ray diffraction in a diamond anvil cell. The graphane II phase did not react with the surrounding hydrogen and did not undergo any phase transformations upon the compression and after heating to 1500 K at 53 GPa. The high thermal and pressure stability of this exotic phase makes it an important part of the C–H system. The obtained g(E) spectra of graphite hydride and deuteride were used to calculate temperature dependences of their heat capacity. Measurements of the heat capacity at temperatures 120–673 K confirmed the good accuracy of these calculations.

Research target: Physics
Language: English
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Keywords: фононыheat capacityтеплоемкостьphononsequation of stateуравнение состояниявысокое давлениеHigh-pressureInelastic neutron scatteringнеупругое рассеяние нейтроновMultilayer graphane, Hydrogen storageМногослойный графан, хранение водорода,
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