1434 papers
Hep-Ex explores the fascinating intersection where particle physics meets experimental reality. This field investigates how scientists build massive detectors and accelerate particles to test the fundamental laws of nature, turning abstract theories into measurable data. It is the rigorous process of searching for new particles or forces that could reshape our understanding of the universe, often requiring years of collaboration and engineering.
At Gist.Science, we ensure these discoveries become accessible to everyone. We process every new preprint in this category directly from arXiv, generating both plain-language explanations for curious readers and detailed technical summaries for specialists. Our goal is to bridge the gap between complex experimental results and public understanding without losing scientific nuance.
Below are the latest papers in Hep-Ex, freshly summarized and ready for you to explore.
This paper presents a physics-informed neural network approach to extract a universal small- dipole scattering amplitude directly from global DIS and photoproduction data without rigid parametric assumptions, successfully resolving the long-standing tension between total and charm cross-section channels while providing a smooth, non-negative input for Color Glass Condensate phenomenology.
Using a large sample of events collected by the BESIII detector, this study presents an improved measurement of the branching fraction for the decay and reports the first determination of its transition form factor cutoff parameter, providing valuable insights into the internal structure of the meson.
This paper demonstrates a novel "tuning-by-opening" mechanism for a NbSn superconducting microwave cavity that achieves continuous frequency tuning exceeding 1 GHz while maintaining a high quality factor suitable for dark matter searches, all without inserting elements into the resonant volume.
Using 137 fb of 13 TeV proton-proton collision data from the ATLAS detector, this study searches for long-lived charginos and -sleptons via disappearing tracks and sets 95% confidence level lower mass limits of up to 880 GeV for wino charginos and 320 GeV for -sleptons, finding no significant excess over Standard Model background predictions.
Using 140 fb⁻¹ of proton-proton collision data at 13 TeV collected by the ATLAS detector, this study searches for Higgs boson decays into pairs of low-mass pseudoscalars that subsequently decay into four tau leptons, finding no significant excess over Standard Model backgrounds and setting 95% confidence level upper limits on the branching fraction between 0.06 and 0.23 for pseudoscalar masses ranging from 15 to 60 GeV.
This paper proposes and demonstrates a constrained end-to-end differentiable framework for High-Energy Physics trigger systems that jointly optimizes all processing stages against a unified physics objective, achieving a 2-4x improvement in true-positive rates for Higgs boson pair production while maintaining interpretability and calibration constraints.
Using 4.4 fb⁻¹ of annihilation data collected by the BESIII detector, this study performs an amplitude analysis of the singly Cabibbo-suppressed decay , resulting in the first observation of and modes, the measurement of branching fractions for several intermediate resonances, and an updated, more precise branching fraction for the overall decay that supersedes previous BESIII results.
This paper calculates enhanced electroweak, QCD, and QED radiative corrections to the nucleon coupling constants and , providing updated relations between lattice-QCD and physical values that yield a total correction of approximately 3.5% to 5.6% and predict a physical axial charge of 1.265(26) or 1.240(9) depending on the input methodology.
Using 9 fb of LHCb $pp$ collision data, this study reports the first observation of the decay and provides improved measurements of branching-fraction ratios for various charmless three-body decays.
This paper characterizes and upgrades a hybrid quantum-classical graph neural network for charged particle track reconstruction in high-luminosity LHC environments, demonstrating improved training convergence and behavior through the integration of parametrized quantum circuits.