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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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The σ− Cohomology Analysis for Symmetric Higher-Spin Fields

Symmetry. 2021. Vol. 13. No. 8. Article 1498.
Bychkov A., Ushakov K., Vasiliev M.

In this paper, we present a complete proof of the so-called First On-Shell Theorem that determines dynamical content of the unfolded equations for free symmetric massless fields of arbitrary integer spin in any dimension and arbitrary integer or half-integer spin in four dimensions. This is achieved by calculation of the respective σ − cohomology both in the tensor language in Minkowski space of any dimension and in terms of spinors in A d S 4 . In the d-dimensional case H p ( σ − ) is computed for any p and interpretation of H p ( σ − ) is given both for the original Fronsdal system and for the associated systems of higher form fields.

Research target: Physics Mathematics
Language: English
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Keywords: cohomologyhigher spin theory
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