26 July 2026 to 1 August 2026
University of Maryland, College Park
US/Eastern timezone

AI-Assisted Higher-Order Hopping-Parameter Expansion in Lattice QCD

31 Jul 2026, 14:20
20m
Benjamin Banneker B (Adele H. Stamp Student Union)

Benjamin Banneker B

Adele H. Stamp Student Union

3972 Campus Dr, College Park, MD 20742
Contributed talk Algorithms and artificial intelligence Algorithms and artificial intelligence

Speaker

Tatsuya Wada (YITP/Kyoto University)

Description

The hopping-parameter expansion (HPE) of the logarithm of the Wilson-fermion determinant expresses the coefficient of $\kappa^n$ as a sum over closed loops of length $n$. It is widely used in studies of heavy-quark QCD and in stochastic estimators of the fermion determinant. Although the expansion through sixth order, corresponding to LO and NLO, is well established, higher-order terms have rarely been constructed because the number of loop classes grows combinatorially. Through a collaboration between human researchers and AI coding agents, we have developed efficient algorithms for evaluating the N$^2$LO–N$^4$LO terms. Starting from a loop classification designed by the researchers, the AI agents proposed a trie-based algorithm that reuses partial matrix products shared by multiple loops, thereby reducing the computational cost of evaluating these higher-order contributions on a given gauge configuration. All results were verified to agree exactly with those obtained using a reliable but computationally expensive reference implementation. In this talk, we present the algorithms and discuss their potential applications.

Author

Tatsuya Wada (YITP/Kyoto University)

Presentation materials

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