5500 papers
Hep-Ph explores the fundamental forces that govern how particles interact and behave at the smallest scales imaginable. This field bridges the gap between theoretical predictions and experimental reality, helping scientists understand the building blocks of our universe without getting lost in complex mathematics. Whether investigating the Higgs boson or searching for new physics beyond current models, these studies push the boundaries of human knowledge about matter and energy.
At Gist.Science, we process every new preprint in this category as soon as it appears on arXiv. We strip away the dense jargon to offer both accessible plain-language explanations and detailed technical summaries, ensuring that groundbreaking research is understandable to everyone from students to seasoned experts. Below are the latest papers in this dynamic field, ready for you to explore with clarity and depth.
Using the constituent quark model, this paper analyzes the radiative decays of various excited and charmed baryons in the flavor anti-triplet, providing branching ratios and decay widths that aid in identifying resonances and clarifying the nature of the and states.
This paper demonstrates that background-inert perturbative couplings in coincident gravity create a degeneracy between the primordial amplitude and the growth factor, leading to unphysically high values that can be resolved by imposing Planck priors, a constraint that ultimately penalizes the extended models with information criteria despite a weak statistical preference for the CDM++ variant.
This paper introduces Collider-Bench, a novel benchmark designed to evaluate the ability of autonomous AI agents to reproduce complex Large Hadron Collider particle physics analyses using public resources, revealing that current general-purpose coding agents still fall short of human physicists in reliably executing these tasks.
This paper presents a formulation of PanScales final-state showers that incorporate massive quarks to achieve next-to-leading logarithmic accuracy while preserving the original accuracy for mass-irrelevant observables, with its validity confirmed through fixed-order tests, all-order resummed comparisons, and phenomenological studies using LEP data.
This paper demonstrates that localized 't Hooft anomalies on extended defects enable "categorical scattering" processes, where incoming particles transform into exotic twist operator states by trapping charges at symmetry junctions, a mechanism illustrated through massless fermion models, new massive integrable theories, and lattice spin chains.
This paper identifies and quantifies a significant new source of millicharged particles at the LHC, demonstrating that secondary showers in the forward TAXN absorber can enhance the expected signal yield for the proposed FORMOSA detector by approximately 50% for light masses, thereby establishing downstream production as a critical component for realistic sensitivity projections in future high-luminosity searches.
This paper proposes a symmetry-guided phenomenological model of pseudo-scalar mesons that combines chiral and heavy-quark flavor symmetries to systematically describe charged-current weak decays, offering a hadron-level framework that naturally incorporates non-factorizable effects and reproduces established heavy-quark scaling relations and isospin sum rules.
This paper introduces a new, physically motivated ansatz called AMA25 for Generalized Parton Distributions (GPDs), which demonstrates superior fit quality, better adherence to theoretical constraints, and enhanced extrapolation stability compared to the previous GSAMA24 model, as validated through efficient computational analysis.
This paper presents a comprehensive analysis of Landau-Khalatnikov-Fradkin transformations in reduced quantum electrodynamics to derive the fermion propagator in arbitrary covariant gauges, identifying as the optimal reference gauge for simplifying perturbative calculations and numerically confirming the gauge invariance of the chiral condensate and fermion pole mass.
This paper proposes a "Double Metric Learning" approach that learns two distinct node representations to resolve conflicts in constructing directed graphs with chain connections for the ATLAS ITk detector, demonstrating improved performance in graph construction and edge direction prediction for high transverse momentum particles compared to simple metric learning.