We introduce free-energy machine (FEM), an efficient and general method for solving combinatorial optimization problems. FEM combines free-energy minimization from statistical physics with gradient-based optimization techniques in machine learning and utilizes parallel computation, outperforming state-of-the-art algorithms and showcasing the synergy of merging statistical physics with machine learning.
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This is a summary of: Shen, Z.-S. et al. Free-energy machine for combinatorial optimization. Nat. Comput. Sci. https://doi.org/10.1038/s43588-025-00782-0 (2025).
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Integrating statistical physics and machine learning for combinatorial optimization. Nat Comput Sci 5, 277–278 (2025). https://doi.org/10.1038/s43588-025-00794-w
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DOI: https://doi.org/10.1038/s43588-025-00794-w