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 calculates radiative transitions within the lowest charmonium-hybrid multiplet using a constituent gluon model based on Coulomb-gauge QCD, finding that results for and agree with quenched lattice computations while the transition is significantly lower than lattice estimates.
This paper extends the Sill distribution to arbitrary partial waves by modifying the propagator's mass term to correctly implement threshold behavior while preserving exact normalization, successfully benchmarking the approach with the -wave description of the resonance.
This paper resolves the Gallium Anomaly by demonstrating that solar neutrino measurements, calibrated via neutrino-electron elastic scattering, show good agreement between observed and expected capture rates, thereby ruling out errors in the Ga cross section or experimental efficiencies as the cause of the discrepancy.
This paper presents a machine-learning-based generative surrogate for charged-current neutrino-nucleus scattering that can be directly calibrated to experimental differential cross sections without event-level data, thereby improving predictions for unmeasured observables and maintaining applicability across different neutrino fluxes.
The MicroBooNE collaboration conducted an inclusive search for anomalous single-photon production to investigate the MiniBooNE low-energy excess, finding overall agreement with predictions but observing a sub-sample of proton-free events with a local significance just above 2 concentrated below 600 MeV.
This paper presents an uncertainty quantification framework applied to the ACORN geometric deep learning tracking pipeline using the TrackML dataset, demonstrating that model performance is well-calibrated and that aleatoric uncertainty dominates as training data increases, indicating the model has reached its full potential.
RINO introduces a novel self-supervised learning framework for high-energy physics that leverages the multi-scale renormalization group structure of jet formation to pretrain models on unlabeled QCD data, achieving superior out-of-distribution classification performance and data efficiency compared to existing methods.
This paper reviews the past 25 years of progress in high-resolution timing, rate capability, and aging performance of particle detectors—focusing on MCP, SiPM, LGAD, 3D silicon, and SiEM technologies compared to gaseous detectors—and presents preliminary Mini-TCAD simulation results suggesting that hexagonal 3D silicon cells offer superior drift-time uniformity and timing resolution compared to square cells.
Using 138 fb of 13 TeV proton-proton collision data, the CMS collaboration conducted a search for resonant and nonresonant production of dijet resonance pairs, setting new limits on diquark and top squark models while observing local excesses with significances of 3.9 and 3.6 standard deviations that remain statistically insignificant globally.
This paper presents a quantum-enhanced search for the Galactic dark-photon background using a superconducting cavity prepared in four-component cat states, leveraging the absence of predicted diurnal modulation in parity measurements to set 90% confidence-level bounds on the kinetic-mixing parameter for relativistic dark photons.