1429 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.
Using 137 fb⁻¹ of 13 TeV proton-proton collision data collected by the ATLAS detector, a search for the lepton-flavour violating decay via the channel found no evidence of signal, setting an observed 90% confidence level upper limit on the branching ratio of .
This review paper synthesizes current theoretical, cosmological, astrophysical, and experimental efforts to explore the theoretically motivated meV axion mass range, highlighting the convergence of diverse approaches aimed at discovering these particles as a key probe for beyond-Standard-Model physics.
This paper introduces ClusTEX, a novel single-step graph transformer that utilizes a geometry-aware positional encoding scheme to outperform standard algorithms and multi-step deep learning approaches in reconstructing overlapping electromagnetic showers, thereby improving energy resolution, reducing splitting rates, and maintaining robustness against detector failures in both toy and ECAL-inspired calorimeter simulations.
This paper presents the first lattice QCD calculation of form factors using 2+1 flavor domain-wall fermions and an anisotropic clover action for the bottom quark, which are then utilized to provide Standard-Model predictions for the branching fractions and angular observables of the rare decays and .
Using 7.33 fb of data collected by the BESIII detector, this study reports the first observation of the decay and measures an unexpectedly large branching fraction for the intermediate process with over significance, providing new constraints on the internal structure of light scalar mesons.
This paper presents a calculation of the corrections to the Higgs boson decay into massive bottom quarks induced by top-quark Yukawa couplings, finding that these contributions increase the decay width by 0.4% and significantly reduce scale dependence to 0.4%, thereby surpassing the precision expected at future lepton colliders.
The ATLAS collaboration presents a combined effective field theory interpretation of vector-boson scattering and tri-boson measurements from 13 TeV proton-proton collisions to constrain anomalous quartic gauge boson couplings arising from dimension-8 operators, providing confidence intervals with and without unitarity constraints.
Using lattice QCD calculations on MILC ensembles with overlap and NRQCD actions, this study provides strong evidence for a deeply bound doubly bottom tetraquark in the isoscalar channel while finding no conclusive evidence for a bottom-strange counterpart.
This paper presents a systematic approach using Loop-Tree Duality to identify and construct finite multiloop Feynman integrals with improved analytic and numerical properties, introducing a generalized set of integrands that are inherently infrared-finite and mitigate problematic ultraviolet behavior.
This paper demonstrates that the Particle Transformer (ParT) significantly outperforms traditional BDT-based taggers for jet flavor identification at Higgs factories, achieving a 5–10-fold improvement in / tagging efficiency while also enabling effective strange tagging and quark/antiquark separation through the integration of multivariate hadron identification data.