2503 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 proposes a hadrophilic gauge extension model featuring exothermic freeze-in dark matter mediated by a boson to simultaneously explain the recent high-energy LZ event and satisfy indirect detection constraints while evading flavor mixing limits.
This paper introduces machine learning models, specifically a tabular diffusion model and a circular spline flow, to generate fast and accurate beam-induced background (BIB) simulations for future Muon Colliders, achieving over an order of magnitude speedup compared to traditional full simulation while maintaining high fidelity for event reconstruction R&D.
This review outlines modern strategies utilizing dispersion relations, lattice gauge theory, and nuclear many-body calculations to reduce hadronic and nuclear uncertainties in radiative corrections for low-energy weak interaction processes, thereby enhancing the precision of searches for physics beyond the Standard Model.
This paper derives a Wandzura-Wilczek-like relation and a Burkhardt-Cottingham-like sum rule connecting the twist-2 and twist-3 tensor-polarized partonic structures of the spin-1 deuteron, and uses HERMES data to phenomenologically estimate that the twist-3 distribution is comparable in magnitude and shape to the twist-2 distribution , suggesting significant subleading-twist effects for future low- experiments.
The paper introduces ResoSeg, a novel deep learning model that combines Transformer and segmentation techniques to perform joint particle-level segmentation and event-level classification for resonance tagging, demonstrating significantly improved efficiency and generalizability in reconstructing decays at the BESIII experiment compared to conventional methods.
This paper presents next-to-leading order perturbative QCD predictions for exclusive heavy-quarkonium electroproduction at HERA to establish benchmarks for future Electron-Ion Collider measurements, while advocating for a dedicated resummation framework to address challenges at large photon virtualities.
Using 138 fb of proton-proton collision data at = 13 TeV collected by the CMS experiment, this study presents a search for a light pseudoscalar Higgs boson in the final state employing novel boosted ditau reconstruction techniques, finding no significant excess over the Standard Model background and setting the first LHC upper limits on such decays for a heavy scalar boson up to 1 TeV.
This paper analyzes 7 TeV proton-proton collision data from the ALICE experiment using a generalized parton model that incorporates parton fusion and compound state formation to explain the scaling dependence of hadron production cross sections for pions, kaons, and antiprotons.
This thesis utilizes 10.67 years of IceCube atmospheric neutrino data to search for an unstable sterile neutrino model, finding no evidence for such decay while significantly constraining the parameter space preferred by short-baseline anomalies, and simultaneously lays the groundwork for future antineutrino resonance searches through improved cross-section calculations, machine-learning reconstruction, and enhanced event selection.
This paper reports the first validation of the NEXT-100 detector's topological discrimination capabilities at low pressure (~4 bar), demonstrating a signal efficiency of 75.6% and background acceptance of 14.7% for distinguishing neutrinoless double beta decay-like events from background, which aligns with the performance of its predecessor, NEXT-White.