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Physical Review D

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Reinforcement learning and metaheuristics for Feynman-integral reduction

Mao Zeng*

  • Higgs Centre for Theoretical Physics, School of Physics and Astronomy, University of Edinburgh, Edinburgh EH9 3FD, United Kingdom

  • *Contact author: mao.zeng@ed.ac.uk

Reinforcement Learning Techniques for the Flavor Problem in Particle Physics

Alessio Giarnetti and Davide Meloni

Symmetry 18 131 (2026)

Notes on Fourier transform and its application to three-point momentum-space integrals

Xuhang Jiang

Phys. Rev. D 113 036012 (2026)

Critical points and syzygies for Feynman integrals

Ben Page and Qian Song

J. High Energ. Phys. 2026 4 (2026)

The spectrum of Feynman-integral geometries at two loops

Piotr Bargieła, Hjalte Frellesvig, Robin Marzucca, Roger Morales, Florian Seefeld, Matthias Wilhelm, and Tong-Zhi Yang

J. High Energ. Phys. 2026 57 (2026)

FIRE 7: Automatic reduction with modular approach

Alexander V. Smirnov and Mao Zeng

Computer Physics Communications 325 110200 (2026)

Kira 3: Integral reduction with efficient seeding and optimized equation selection

Fabian Lange, Johann Usovitsch, and Zihao Wu

Computer Physics Communications 322 109999 (2026)

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