Matthias Wilhelm

CR
h-index9
3papers
85citations
Novelty33%
AI Score23

3 Papers

HEP-THFeb 7, 2025
Refining Integration-by-Parts Reduction of Feynman Integrals with Machine Learning

Matt von Hippel, Matthias Wilhelm

Integration-by-parts reductions of Feynman integrals pose a frequent bottle-neck in state-of-the-art calculations in theoretical particle and gravitational-wave physics, and rely on heuristic approaches for selecting integration-by-parts identities, whose quality heavily influences the performance. In this paper, we investigate the use of machine-learning techniques to find improved heuristics. We use funsearch, a genetic programming variant based on code generation by a Large Language Model, in order to explore possible approaches, then use strongly typed genetic programming to zero in on useful solutions. Both approaches manage to re-discover the state-of-the-art heuristics recently incorporated into integration-by-parts solvers, and in one example find a small advance on this state of the art.

LGMay 9, 2024
Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory

Tianji Cai, Garrett W. Merz, François Charton et al.

We pursue the use of deep learning methods to improve state-of-the-art computations in theoretical high-energy physics. Planar N = 4 Super Yang-Mills theory is a close cousin to the theory that describes Higgs boson production at the Large Hadron Collider; its scattering amplitudes are large mathematical expressions containing integer coefficients. In this paper, we apply Transformers to predict these coefficients. The problem can be formulated in a language-like representation amenable to standard cross-entropy training objectives. We design two related experiments and show that the model achieves high accuracy (> 98%) on both tasks. Our work shows that Transformers can be applied successfully to problems in theoretical physics that require exact solutions.

CROct 1, 2019
Insights into the Mind of a Trojan Designer: The Challenge to Integrate a Trojan into the Bitstream

Maik Ender, Pawel Swierczynski, Sebastian Wallat et al.

The threat of inserting hardware Trojans during the design, production, or in-field poses a danger for integrated circuits in real-world applications. A particular critical case of hardware Trojans is the malicious manipulation of third-party FPGA configurations. In addition to attack vectors during the design process, FPGAs can be infiltrated in a non-invasive manner after shipment through alterations of the bitstream. First, we present an improved methodology for bitstream file format reversing. Second, we introduce a novel idea for Trojan insertion.