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News
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.

 

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Лекции по физике поверхности

Н. Новгород : Национальный исследовательский Нижегородский государственный университет им. Н.И. Лобачевского, 2024.
Aladyshkin A. Y., Фраерман А. А.
Under the general editorship: Е. З. Грибова
Research target: Physics
Language: Russian
Sample Chapter
Full text
Keywords: коалесценциясканирующая туннельная микроскопиямодель Изингадоменная сверхпроводимостьповерхностное натяжениемалоугловое рассеяниеэффект близостипереход Пайерлсасканирующая туннельная спектроскопияповерхностная сверхпроводимостьшероховатая поверхностьпромежуточное состояние сверхпроводникаотражение рентгеновского излученияприближение сплошной средыборновское приближениемногослойные структурыдлина экстинкциикоррелированные шероховатостирассеяние электронов на кристаллической решёткедифракция медленных электроновдифракция быстрых электроновотражение тепловых нейтроновферромагнитные поляризаторы нейтроновтуннельное магнитосопротивлениеповерхностные электронные состояния Тамма-Шоклиповерхностные состояния в потенциале изображенияинтерференция поверхностных квазичастицприкраевая сверхпроводимостьравновесная форма кристалловтеорема Вульфакраевой угол Юнгафазовый переход поверхности в шероховатое состояниемеханизмы релаксации поверхностных шероховатостейдислокации несоответствиямодель Френкеля–Конторовойпсевдоморфный росткритическое рассогласованиекритическая толщинамодели роста кристалловмодель Колмогоровамодель Лифшица-Слёзовараспад твёрдых растворовмодель Кана–Хиллардадоменная структура ферромагнетиковдоменная стенкамагнитно-силовая микроскопияфазовое расслоение в сверхпроводникахэффект Мейсснерачастица в мелкой яметеорема Полиа
Лекции по физике поверхности
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Numerous studies have provided compelling evidence that the probability distribution of avalanche sizes follows a power law, and that 1/f noise is present in the stochastic dynamics of landslides. We present a theoretical explanation of these phenomena within the framework of self-organized criticality theory, proposing a discrete-time model in the form of a sandpile cellular ...
Added: October 13, 2026
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A discrete-time model is presented for the self-organization of the X/Twitter social network to the edge of a phase transition, characterized by avalanche-like propagation of information in the network. The model is based on the analogy between the critical dynamics of the X social network and sandpile cellular automata with Manna rule on the Chung-Lu ...
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Superconducting properties of metallic micro- and nanowires can be entirely different from those of bulk superconductors. Of particular interest is the nonequilibrium current-induced state of a quasi-one-dimensional superconducting channel. The most interesting phenomenon here is the stepped I–V characteristic, explained by a process known as phase slip center activation. If the origin of such step-like ...
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Machine learning (ML) has become a powerful tool for accelerating the development of carbon-based supercapacitors; however, most published models assume that a single predictive framework can describe both conventional porous carbons and hybrid carbon electrodes. Here, we test this assumption using a comprehensive benchmark dataset and an extended literature-curated dataset enriched with synthesis- and electrolyte-related descriptors. Three ML algorithms ...
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On the Validity of Transfer Learning for Temperature and Critical Exponent Extraction
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In this manuscript we consider a superconducting film in the vicinity of the critical temperature and presence of the proximity effect. We analytically solve the corresponding linearized Usadel equation and the self-consistency equation, defining the critical temperature. This is a system of coupled differential and integral equations for the anomalous Green's function and the order parameter of ...
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Supervised Learning in Critical Phenomena—Statistical and Systematic Accuracy
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Supervised machine learning is successfully applied to the study of critical phenomena and allows us to obtain a numerical estimate of the phase transition temperature and the correlation length exponent. We discuss the influence of possible systematic errors, as well as statistical errors, on the accuracy of such numerical estimates. Errors in the training and ...
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Strain-induced superconducting proximity effect in the topological insulator TaSe3
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The magnetoresistance of superconductor–topological insulator–superconductor structures, with indium as the superconductor and TaSe3 as the topological insulator, shows steplike features on the resistance under magnetic fields. These resistance steps result from the suppression of superconductivity, induced by the superconducting proximity effect in both the bulk and surface states of the topological insulator. The position and ...
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This work demonstrates that depositing a thin layer of Mo (5–15 nm) onto a 10 nm thick NbN strip leads to a significant increase in the nonlinearity of the kinetic inductance . Specifically, the change in  with increasing current reached 70% in the NbN/Mo bilayer at liquid helium temperature, whereas in the NbN strip,  changed by only 10% ...
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We develop a linear response theory for the dynamical proximity effect in topological superconductor/ferromagnetic insulator (TS/FI) hybrids. Our approach integrates the nonequilibrium quasiclassical Keldysh-Usadel formalism for the TS with the Landau-Lifshitz-Gilbert equation for the FI's magnetization dynamics. This framework reveals a proximity-induced coupling between magnons and superconducting collective modes. Crucially, we find that spin-momentum locking in ...
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Shapiro Steps in ballistic Josephson junction based on a single Bi2Te2.3Se0.7 nanocrystal
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Superconducting proximity junctions based on topological insulators are widely believed to harbor Majorana-like bound states. If so, the static current phase relationship (CPR) should have a 4π-periodic component. It is then usually assumed that the static CPR can be extended to treat dynamic, voltage-biased, experiments and can justify the suppression of the first phase-lock-in microwave ...
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In this review, we summarize the foundations underlying a variety of phenomena in superconductor– ferromagnet hybrid structures, with a focus on recent advances in several key areas. These include: (i) the fundamental understanding of proximity effects in superconductor–ferromagnet based systems; (ii) spin-valve effects in superconductor– ferromagnet and superconductor–ferromagnet–superconductor Josephson junctions; and (iii) the design and ...
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In the ballistic regime at finite temperatures, the proximity effect diminishes following an exponential pattern; however, at low or zero temperatures, this transition alters to a decay characterized by a power law with a dimensionality-dependent exponent. Here, we extend the current understanding of the proximity effect by exploring the role of normal metal–superconductor (NS) junction ...
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Extraction of properties of anisotropic spin model by deep transfer learning methods
D.D. Sukhoverkhova, L.N. Shchur, , in: Параллельные вычислительные технологии – XIX всероссийская конференция с международным участием, ПаВТ'2025. Короткие статьи и описания плакатов.: Издательский центр ЮУрГУ, 2025. P. 82–89.
We apply supervised deep machine learning techniques to extract properties of the anisotropic Ising model. We consider two cases of anisotropy: orthogonal and diagonal. From the predictions of the neural network, we obtained phase probability functions, from which we measured two quantities: the critical temperature and the critical exponent of the correlation length. We estimated ...
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Interference-induced surface superconductivity (SC), in which the surface critical temperature $T_{cs}$ is enhanced relative to the bulk critical temperature $T_{cb}$, has been predicted recently, sparking intensive studies of its properties within an attractive Hubbard model with $s$-wave pairing. However, a complete understanding of how the relative enhancement $\tau = (T_{cs} - T_{cb})/T_{cb}$ depends on microscopic ...
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Селезнёв Д. В., Seidov S., Pugach N. et al., Известия Уфимского научного центра РАН 2025 № 1 С. 5–11
Рассматривается спиновый вентиль, состоящий из одного сверхпроводящего слоя и двух ферромагнитных изоляторов по краям сверхпроводника. Контакт рассмотрен в грязном пределе, в котором функция Грина сверхпроводника подчиняется уравнению Узаделя. Уравнения Узаделя дополнены соответствующими граничными условиями, моделирующими эффект близости сверхпроводника с ферромагнитным изолятором. Исследование системы проводилось путем численного решения уравнений Узаделя вкупе с уравнением самосогласования для сверхпроводящего параметра порядка. Численный ...
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Machine learning is a new tool for investigating physical models. One possible applications is the study of phase transitions analyzing the distribution of spins on regular lattices using supervised learning approach. A new question is the applicability of transfer learning, a network supervised on a particular model and used to infer information about another model. The ...
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Transfer Machine Learning of an Anisotropic Model
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We investigate the possibility of extracting features  of second-order phase transitions using transfer machine learning. We have performed supervised machine learning for binary classification of snapshots of the spin distribution of the isotropic Ising model. The binary classification is performed in ferromagnetic and paramagnetic phases using a known critical temperature. The trained network is used ...
Added: January 13, 2025
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Лекомцев Н. В., Pugach N., В кн.: Межвузовская научно-техническая конференция студентов, аспирантов и молодых специалистов имени Е.В. Арменского. Москва, 2024.: М.: ООО "Издательский дом Медиа паблишер", 2024. С. 216–218.
The study investigates the controllable proximity effect regulated by spin switching in a superconductor-helimagnet bilayer, comparing the calculated critical parameters of the structure with experimental data. The research is conducted as part of the development of a superconducting spin valve model ...
Added: December 7, 2024
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Detailed analysis of scanning probe microscopy (SPM) data acquired for faceted and non-flat surfaces is usually complicated due to the presence of a large number of surface areas tilted by large/variable angles relative to the scanning plane. As a consequence, standard methods of elimination of global or local slopes by either a plane subtraction or ...
Added: November 27, 2024
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