630 papers
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.
This paper demonstrates that in a 2D quantum Ising model, specific initial-state entanglement—not merely entanglement entropy—suppresses false-vacuum decay to stabilize system-size macroscopic clusters, thereby offering a passive mechanism for preserving global information in quantum many-body systems.
This paper employs a finite-volume formalism incorporating left-hand-cut effects from one-pion exchange to analyze lattice QCD data at the SU(3)-symmetric point, revealing that these effects produce a mild but statistically significant impact on the binding energy of the -dibaryon compared to standard Lüscher quantization methods.
This paper proposes a novel inverse problem framework for calculating non-perturbative QCD quantities by deriving them from high-energy perturbative inputs, utilizing Tikhonov regularization to stabilize the inherently ill-posed problem and demonstrating its efficacy through toy models.
This paper investigates a (1+1)D lattice gauge theory with dynamical matter and static background charges, revealing a dynamical phase diagram that includes ergodic, nonthermal fragmented, and disorder-free many-body localized regimes, where the latter preserves spatial inhomogeneities through superpositions of gauge superselection sectors.
This paper introduces a normalizing flow framework for efficiently calculating all-orders QED corrections in lattice field theory, demonstrating significantly reduced variance across multiple dimensions and the ability to scale from small to large lattices without additional Monte Carlo sampling.
This paper motivates the use of quantum simulation to overcome the exponential computational scaling limitations of classical lattice field theory in studying dense matter and dynamical phenomena, while reviewing current theoretical, algorithmic, and hardware progress and outlining future challenges and opportunities.
This paper proposes a data-driven strategy to predict decays by explicitly incorporating hadronic resonance contributions, such as those from , rather than avoiding them, thereby enabling the use of hadron-collider data and enhancing sensitivity to large New Physics effects across the full kinematic spectrum.
This paper proposes a first-principles framework using gradient flow and renormalization group transformations to analytically derive confinement in QCD, demonstrating that a scale-invariant gluon condensate drives the running coupling to an infrared fixed point consistent with infrared slavery.
The paper argues that analytically continuing Euclidean lattice quantum field theory directly into Minkowski space via inverse Wick rotation is impossible due to nonlocal form factors introduced by discretization, necessitating a prior continuum limit.
This paper demonstrates that autoregressive neural networks can efficiently estimate reduced density matrices and calculate the continuum limit of bipartite entanglement entropies for quantum spin chains by leveraging their correspondence with classical two-dimensional systems, requiring only a single training session for a fixed discretization and volume.