2610 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 novel fast simulation tool for the LHCb experiment that utilizes heterogeneous graph neural networks to emulate detector responses for arbitrary multibody decay topologies, enabling generalizable interpolation to unseen channels and offering a scalable solution to the growing computational demands of particle physics simulations.
This paper demonstrates the application of Truncated Marginal Neural Ratio Estimation (TMNRE) within the Swyft framework to constrain axion-like particle parameters using simulated Cherenkov Telescope Array observations of NGC 1275, showcasing a robust alternative to standard likelihood-based methods for handling complex models with numerous nuisance parameters.
This paper reports the first muon detection efficiency measurements and demonstrates a 75% fill factor-normalized efficiency with 130 ps time resolution for an 8-channel WSi superconducting microwire array, marking a significant step toward high-efficiency charged particle tracking systems for future accelerator experiments.
This paper introduces DUNE-GPT, a prototype framework that utilizes large language models and retrieval-augmented generation to enable secure, natural-language querying of the Deep Underground Neutrino Experiment's extensive documentation and technical resources, thereby enhancing collaboration productivity and onboarding.
This paper demonstrates the successful fabrication and characterization of a hybrid-contact planar HPGe detector (KL01) that combines a lithium-suspension paint process with thin-film a-Ge/Al contacts, validating a practical workflow for future scalable ring-contact designs essential for high-sensitivity rare-event searches.
This paper presents a concise overview of the design and current development status of the Silicon Vertex Tracker (SVT), a key component of the ePIC detector system at the future Electron-Ion Collider that utilizes Monolithic Active Pixel Sensors across its Inner Barrel, Outer Barrel, and Forward/Backward Disks to achieve high-precision tracking with minimal material budget.
This paper reports the first efficient laser cooling, state preparation, and high-resolution spectroscopy of a single trapped ion, enabling the precise measurement of the 436 nm electric quadrupole transition and the hyperfine structure of the state to determine the nuclear magnetic octupole moment with unprecedented accuracy.
This paper outlines the novel strategy developed by the LHCb experiment during Run 2 to select and process calibration samples using a dedicated online-offline computing model, enabling precise measurement of particle identification performance and data-quality monitoring across various decay channels.
This review summarizes the most recent results from the D0, CDF, ATLAS, and CMS experiments at the Tevatron and LHC colliders regarding the properties of the top quark, the heaviest known elementary particle and a key probe for new physics.