Hep-Lat, short for High Energy Physics – Lattice, explores the fundamental forces of nature by simulating particle interactions on a digital grid. Instead of relying solely on abstract equations, researchers in this field use powerful computers to model how quarks and gluons bind together, offering deep insights into the structure of matter that are often impossible to derive analytically.

Gist.Science ensures these complex discoveries from arXiv remain accessible to everyone. We process every new preprint in this category as it is posted, providing both plain-language explanations for the curious and detailed technical summaries for experts. This dual approach bridges the gap between cutting-edge simulation work and broader scientific understanding.

Below are the latest papers in High Energy Physics – Lattice, curated directly from arXiv and ready for you to explore.

⚛️ lattice

U(1) lattice gauge theory and string roughening on a triangular Rydberg array

This paper demonstrates that a triangular Rydberg array can serve as an analog quantum simulator for (2+1)D U(1) lattice gauge theory, naturally realizing string roughening phenomena such as logarithmic width growth and the Lüscher correction, while also enabling the observation of real-time string fluctuations and breaking dynamics.

Lisa Bombieri, Torsten V. Zache, Hannes Pichler, Daniel González-Cuadra2026-02-09
🔬 condensed matter

Automatic Structural Search of Tensor Network States including Entanglement Renormalization

This study presents an algorithm for the automatic structural search of tensor network states, including entanglement renormalization, which optimizes local structures based on variational energy to improve accuracy in representing non-uniform entangled states, particularly when initialized with existing design methods like the strong disordered renormalization group.

Ryo Watanabe, Hiroshi Ueda2026-02-06
⚛️ lattice

Reducing the Computational Cost Scaling of Tensor Network Algorithms via Field-Programmable Gate Array Parallelism

This paper proposes a fine-grained parallel tensor network design utilizing FPGAs and a quad-tile partitioning strategy to drastically reduce the computational cost scaling of iTEBD and HOTRG algorithms from O(Db3)O(D_b^3) to O(Db)O(D_b) and from O(Db6)O(D_b^6) to O(Db2)O(D_b^2), respectively, thereby offering a scalable hardware solution for large-scale quantum many-body calculations.

Songtai Lv, Yang Liang, Rui Zhu, Qibin Zheng, Haiyuan Zou2026-02-06
⚛️ lattice

Spontaneous Parity Breaking in Quantum Antiferromagnets on the Triangular Lattice

This paper demonstrates that spontaneous parity breaking serves as a systematic guiding principle for predicting and rationalizing the emergence of nontrivial phases, such as intermediate-spin parity-broken states and bilayer supersolids, in frustrated quantum antiferromagnets on triangular lattices, a conclusion validated by large-scale tensor network calculations.

Songtai Lv, Yuchen Meng, Haiyuan Zou2026-02-06