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Nuclear Modification Factor of Neutral Pions in the Forward and Backward Regions in p−Pb Collisions
Physical Review Letters. 2023. Vol. 131. No. 4. Article 042302.
Aaij R., Abdelmotteleb A. S., Abellan Beteta C., Abudinén F., Ackernley T., Adeva B., Adinolfi M., A. Boldyrev, M. Hushchyn, M. Karpov, S. Mokhnenko, F. Ratnikov, A. Ryzhikov
Mylnikov L., Slivnitsin P., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185
The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...
Added: May 29, 2026
Borisov V., Danilov V., Электросвязь 2025 № 12 С. 73–84
Представлены результаты математического моделирования процесса полевой эмиссии из катода малых размеров – одного из основных физических процессов, обеспечивающих работы многих электронных устройств, в частности FED-дисплеев (устройства, работающие на принципе полевой эмиссии), кантилеверов и т.д. Дается краткий обзор текущих результатов в области исследования, обосновывается актуальность задачи, приводятся примеры наиболее вероятного использования результатов решения задачи. Обсуждаются физические ...
Added: May 29, 2026
Mokienko O., Zisman M. A., Bobrov P. et al., American Journal of Physical Medicine and Rehabilitation 2026 Vol. 105 No. 6 P. 555–563
Brain-computer interfaces (BCIs) represent a promising technology for restoring lower limb motor functions and gait after stroke. The application of BCIs in this field is supported by a limited number of studies. The objective of the review was to systematically and critically evaluate the current evidence on the use of BCIs for lower limb function ...
Added: May 28, 2026
Arutyunov K., JIANG1 Q., FANG J. et al., Science China Information Sciences 2026 Vol. 69 No. 6 P. 1–11
Resonators based on nanoelectromechanical systems (NEMS) using two-dimensional (2D) materials with high-quality factors and excellent electrical control are critical for tunable coherent phonon dynamics, resonant sensors and wireless communications. However, their performance is fundamentally limited by the lack of a unified framework governing energy dissipation mechanisms and their electrical tunability. Here, we synergistically modulate both ...
Added: May 28, 2026
Elesin L., Shilov A., Jana S. et al., Advanced Functional Materials 2026 P. 1–10
Thermoelectric materials, long explored for energy harvesting and thermal sensing, convert heat directly into electrical signals. Extending their application to the terahertz (THz) frequency range opens opportunities for low-noise, bias-free THz detection, yet conventional thermoelectrics lack the sensitivity required for practical devices. Thermoelectric coefficients can be strongly enhanced near van Hove singularities (VHS), though these ...
Added: May 28, 2026
М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024.
В сборник вошли материалы VIII Международной научной конференции «Информационные технологии и технические средства управления» (ICCT-2024). На конференции были рассмотрены вопросы, касающиеся перспектив развития научного приборостроения в телекоммуникационных и управляющих системах, биомедицинской информатики, аппаратного и программного обеспечения информационнокоммуникационных систем, надежности, диагностики и неразрушающего контроля, систем управления и автоматизации, цифровых экосистем, управления производством и логистикой, методов математического ...
Added: May 27, 2026
Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6
This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
Added: May 26, 2026
Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114
This paper examines echo state networks (ESNs), one of the most prevalent approaches to
implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained)
weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...
Added: May 26, 2026
Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94
В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...
Added: May 24, 2026
Qian X., Deng Y., Shchur L. et al., Physica A: Statistical Mechanics and its Applications 2026 Vol. 696 P. 1–13
We perform a Monte Carlo analysis of the Ising model on many three-dimensional lattices. By means of finite-size scaling we obtain the critical points and determine the scaling dimensions. As expected, the critical exponents agree with the three-dimensional Ising universality class for all models. The irrelevant field, as revealed by the correction-to-scaling amplitudes, appears to ...
Added: May 24, 2026
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118
This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...
Added: May 22, 2026
Jin S., Komarov M. M., Scientific Reports 2026
Intrabody communication (IBC) channels offer physiological diversity that can be leveraged for passive biometric identification in wearable devices. Recent reports of over 99 per cent identification accuracy have frequently resulted from data leakage, where samples from the same subject are seen in both training and evaluation, yielding inflated and unreliable metrics. In this work, we ...
Added: May 21, 2026
Melentiev P. N., Калмыков А. С., Гритченко А. С. et al., Успехи физических наук 2024 Т. 194 № 11 С. 1130–1145
Представлен краткий обзор достигнутого уровня оптических методов детектирования единичных молекул в биомедицинских приложениях. Показано, что регистрация флуоресценции единичных молекул красителей, ковалентно связанных с антителами (биомолекулами), совместно с использованием современных методов нанофотоники может быть применена для решения различных задач в биологии и медицине: визуализации биомолекул, токсинов, вирусных частиц, определения ультранизких концентраций аналитов напрямую во взятой пробе, ...
Added: May 21, 2026
Aehle M., Arsini L., Belén Barreiro R. et al., Reviews in Physics 2025 Vol. 13 Article 100120
In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models we consider rely on differentiable programming methods and on the specification of a software pipeline including all factors impacting performance — from the data-generating processes to their reconstruction and ...
Added: June 15, 2025
Derkach D., Kazeev N., Mokhnenko S. et al., EPJ Web of Conferences 2024 Vol. 295 P. 03040
Detailed detector simulation is the major consumer of CPU resources at LHCb, having used more than 90% of the total computing budget during Run 2 of the Large Hadron Collider at CERN. As data is collected by the upgraded LHCb detector during Run 3 of the LHC, larger requests for simulated data samples are necessary, ...
Added: January 8, 2025
Ali S., Ryzhikov A., Derkach D. et al., Moscow University Physics Bulletin 2024 Vol. 79 No. Suppl. 2 P. S591–S597
In the realm of high-energy physics, the longevity of calorimeters is paramount. Our research introduces a deep learning strategy to refine the calibration process of calorimeters used in particle physics experiments. We develop a Wasserstein GAN inspired methodology that adeptly calibrates the misalignment in calorimeter data due to aging or other factors. Leveraging the Wasserstein ...
Added: November 7, 2024
Rogachev A., Ratnikov F., Computing and Software for Big Science 2024 Vol. 8 No. 1 Article 12
In this paper, we explore the use of Generative Adversarial Networks (GANs) to speed up the simulation process while ensuring that the generated results are consistent in terms of physics metrics. Our main focus is the application of spectral normalization for GANs to generate electromagnetic calorimeter (ECAL) response data, which is a crucial component of ...
Added: July 2, 2024
Rogachev A., Ratnikov F., EPJ Web of Conferences 2024 Vol. 295 Article 09007
High energy physics experiments heavily rely on the results of MC simulation of data used to extract physics results. However, the detailed simulation often requires tremendous amount of computation resources.
Using Generative Adversarial Networks and other deep learning generative techniques can drastically speed up the computationally heavy simulations like a simulation of the calorimeter response. To ...
Added: May 20, 2024
Aaij R., Abdelmotteleb A. S., Abellan Beteta C. et al., Chinese Physics C 2023 Vol. 47 No. 9 Article 093001
https://iopscience.iop.org/article/10.1088/1674-1137/ace9c8#artAbst ...
Added: December 4, 2023
Aaij R., Abdelmotteleb A. S., Abellan Beteta C. et al., Physical Review D - Particles, Fields, Gravitation and Cosmology 2023 Vol. 108 No. 1 Article L011103
https://journals.aps.org/prd/abstract/10.1103/PhysRevD.108.L011103 ...
Added: December 4, 2023