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November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
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Excess momentum or excess inertia: Do companies adopt technologies at the right time?

European Research on Management and Business Economics. 2021. Vol. 27. No. 3. Article 100174.
Daviy A., Shakina E.

Drawing on the literature on organizational change, technological change, and inertia, this paper explores how the moment that companies choose to initiate a technological change relative to other companies from the same regional and industrial context influences the company's performance. In particular, we test the excess inertia and excess momentum phenomena that refer to timely and untimely technological shifts in companies. A data set comprising about 1000 of the largest Russian companies, affiliated with 19 industries, located in most of the Russian regions, for 10 years starting from 2008, is used. Applying a multi-level approach of hierarchical linear modeling, we estimated the region environment effect and the industry effect on sales and productivity. The use of moderation effects of the correspondent technology adoption with the average lag or lead from the representative company in the industry or region, could help us demonstrate what digital technologies are probably associated with the excess inertia and the excess momentum phenomena on the industry and regional level. The results reveal that the industry effect is a major determinant of firm productivity, whereas sales are mainly influenced by the region effect. Our investigation also found that companies are more likely to exhibit excess inertia rather than excess momentum.

Research target: Economics and Management
Language: English
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Keywords: organizational changetechnological changetime factordigital transformation
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