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 self-supervised learning framework using VICReg and transformer encoders to pre-train models on corrupted data, demonstrating that this approach yields more robust and accurate heavy resonance mass reconstruction in complex cascade decays compared to traditional supervised training.
This paper introduces a data-driven, augmentation-free self-supervised pre-training method for the Large Hadron Collider that pairs distinct events based on their Energy Mover's Distance similarity to learn invariant representations, achieving downstream performance comparable to or better than traditional augmentation-based baselines while preserving event fidelity.
This paper utilizes a species-resolved anisotropy-response scaling framework to demonstrate that the meson in high-multiplicity p+Pb collisions exhibits a single-meson-like response with weak final-state sensitivity, thereby distinguishing its formation dynamics from a molecular structure and establishing this scaling method as a novel experimental probe.
Inspired by the recent LHCb observation of , this study utilizes the one-boson-exchange framework to propose that the state is a molecule and predicts the existence of several related molecular partners to guide future experimental searches.
This paper challenges the long-held assumption that nuclear modifications do not affect the longitudinal-transverse structure-function ratio by demonstrating, through a convolution model of nucleon Fermi motion in the deuteron, that the mixing of longitudinal and transverse components and differing -dependencies lead to significant nuclear effects that are currently being investigated experimentally at Jefferson Lab.
This paper presents Geant4 simulations demonstrating that cosmic-ray muon backgrounds in Atomki's e+e- pair spectrometers can produce statistically significant excesses in opening-angle distributions that closely mimic the reported 17 MeV boson anomaly, suggesting that cosmic rays may be a dominant source of the observed signal rates.
This paper establishes a systematic formalism for matching long-wavelength correlations between incoming nuclear ground states and final-state multi-particle observables in relativistic collisions by constructing detector correlators from asymptotic energy flows and mapping them to multipole-operator correlators derived from small- QCD.
This paper introduces VyPER, a novel geometric learning framework that combines hypergraph representation learning with graph-conditioned diffusion models to simultaneously optimize particle assignment and neutrino kinematics prediction, demonstrating superior event reconstruction performance across diverse Standard Model processes compared to existing techniques.
This paper establishes a theoretical framework for analyzing Abelian charge fluctuations in nuclear collisions by deriving analytical expressions for cumulants in the canonical ensemble and incorporating local multi-particle interactions, which successfully reproduce STAR and HADES experimental data by revealing the decisive role of repulsive two-proton interactions at high energies and attractive three-particle interactions at lower energies.
This paper introduces the LENS technique, which utilizes off-axis neutrino beam measurements to independently constrain meson flux models and subsequently improve the precision of far-detector flux predictions for long-baseline oscillation experiments.