5243 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.
This paper reviews recent progress in meson photoproduction at Jefferson Lab, highlighting the understanding of the system and deriving the complete angular distribution for the reaction as a crucial step toward searching for exotic hybrid mesons in the channel.
This paper utilizes the xFitter framework to demonstrate that resummation-scale variations, a previously unaccounted theoretical uncertainty in parton distribution function determinations, significantly impact LHC top-quark pair production predictions and must be included in precision QCD analyses.
This paper reanalyzes the LUX-ZEPLIN (LZ) experiment's single nuclear-recoil candidate by incorporating a two-state dark matter halo model, demonstrating that the presence of a small fraction of excited dark matter states can significantly lower the required scattering cross-section and alter kinematic constraints compared to standard interpretations.
This paper introduces a new perturbative framework that defines an in-medium jet function to extend the BDMPS-Z formalism, enabling a virtuality-resolved description of jet propagation in heavy-ion collisions that elucidates the interplay between vacuum-like evolution and medium-induced dynamics.
This paper demonstrates that combining Gaia-informed galactic dynamics with LUX-ZEPLIN data reveals a suppressed high-velocity dark matter tail, which significantly alters the particle-physics interpretation of the LZ230616 high-energy recoil event, particularly by requiring larger scattering cross sections for endothermic dark matter scenarios unless the gravitational influence of the Large Magellanic Cloud is accounted for.
This paper introduces a new algorithm implemented in the Alaric code for simulating massive parton evolution in QCD, which utilizes azimuthal-dependent splitting functions and a symmetry-preserving kinematic mapping to achieve differentially accurate soft-gluon radiation, fully differential NLO matching, and NLL-accurate parton showers validated against experimental data.
Fully non-linear numerical simulations reveal that while shift-symmetric Einstein-scalar-Gauss-Bonnet gravity accelerates the merger of black hole binaries compared to general relativity due to scalar dipole radiation, strong-field conservative dynamics significantly suppress this acceleration, resulting in a slower merger phase than predicted by post-Newtonian approximations.
The paper introduces MAGGIE, a novel European lumped-element experiment utilizing a 14 T solenoid and a specialized figure-8 pickup loop to detect high-frequency gravitational waves in the kHz–MHz range by measuring GW-induced electromagnetic currents, with projected sensitivities capable of constraining unexplored parameter spaces for both transient and continuous signals.
This paper demonstrates that a unified physics-informed neural network can robustly recover the time-time component of static, spherically symmetric black-hole exterior metrics across a wide radial range and various charge and cosmological-constant configurations, achieving low relative errors without relying on domain partitioning or labeled field data.
This paper proposes a post-hoc reweighting scheme using cell-based resampling and Optimal Transport metrics to mitigate the statistical inefficiency caused by negatively weighted events in high-precision Monte Carlo simulations, demonstrating its effectiveness on NLO Z+jets data.