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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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Unexpected magnetic phase in the weakly ordered spin-1/2 chain cuprate Sr2CuO3

Physical Review B: Condensed Matter and Materials Physics. 2020. Vol. 101. P. 201107–201107.
Sergeicheva E. G., S.S. Sosin, Zaliznyak I. A., Gorbunov D. I., Zherlitsyn S., Gu G. D.

The magnetic phase diagram of a spin-12 chain antiferromagnet Sr2CuO3 is studied by an ultrasound phase-sensitive detection technique. The system is in the extreme proximity of the Luttinger-liquid quantum-critical point and we observe an unusually strong effect of magnetic field, which is very weak compared to the in-chain interaction, on the Néel ordering temperature. Inside the ordered phase, we detect an unexpected, field-induced continuous phase transition. The transition is accompanied by softening of magnetic excitation observed by electron-spin resonance, which in previous work [E. G. Sergeicheva et al., Phys. Rev. B 95, 020411(R) (2017)] was associated with a longitudinal (amplitude) mode of the order parameter. These results suggest a transition from a transverse collinear antiferromagnet to an amplitude-modulated spin-density-wave phase in a very weak magnetic field, which is unexpected for a system of weakly coupled Heisenberg spin-12 chains.

Research target: Physics
Language: English
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Keywords: Phase diagramsquantum phase transitionsantiferromagnets
Publication based on the results of:
Topics in condensed-matter physics (2020)
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