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.

⚛️ high-energy experiments

Structure-dependent radiative corrections to e+eπ+πγe^+ e^- \to \pi^+ \pi^- \gamma in the GVMD approach

This paper computes next-to-leading order radiative corrections to the e+eπ+πγe^+ e^- \to \pi^+ \pi^- \gamma process by incorporating the non-perturbative pion structure via the generalized vector meson dominance model, comparing these results with the naive scalar QED approach to quantify model uncertainties for radiative return experiments at flavor factories.

Carlo M. Carloni Calame, Marco Ghilardi, Andrea Gurgone, Guido Montagna, Mauro Moretti, Oreste Nicrosini, Fulvio Piccini (…)2026-03-31
⚛️ high-energy experiments

Assessing (H)EFT theory errors by pitting EoM against Field Redefinitions

This paper proposes a method to assess theoretical uncertainties in Effective Field Theories by leveraging the invariance of physical observables under field redefinitions to validate power-counting schemes and generalize uncertainty estimation from the Standard Model to non-renormalisable interactions, demonstrated through a case study in Higgs Effective Field Theory.

Rodrigo Alonso, Christoph Englert, Wrishik Naskar, Shakeel Ur Rahaman2026-03-30
⚛️ nuclear theory

Benchmarking neutrino-nucleus quasielastic scattering model predictions against a missing energy profile obtained using a monoenergetic neutrino beam

This paper benchmarks three exclusive nuclear ground-state shell models implemented in the NEUT neutrino event generator against recent JSNS2^2 measurements of missing energy from a monoenergetic neutrino beam, finding that spectral function models outperform relativistic mean field models and that accounting for missing energy thresholds allows all tested nuclear models to be statistically accepted.

Jake McKean, Laura Munteanu, Seisho Abe2026-03-30
⚛️ high-energy experiments

Vision Transformers and Graph Neural Networks for Charged Particle Tracking in the ATLAS Muon Spectrometer

This paper presents two machine-learning approaches for the ATLAS Muon Spectrometer to address High-Luminosity LHC challenges: a Graph Neural Network that improves background-hit rejection and reconstruction speed by 15%, and a Vision Transformer proof-of-concept achieving 98% tracking efficiency in just 2.3 ms.

Jonathan Renusch (on behalf of the ATLAS Collaboration)2026-03-30
⚛️ phenomenology

Prying Open the Dark Sector Window with SBND Off-Target Mode

This paper demonstrates that operating the Short-Baseline Near Detector (SBND) at Fermilab in off-target or beam-dump configurations significantly suppresses neutrino-induced backgrounds, thereby substantially extending its sensitivity to probe various new physics scenarios such as light dark matter, axion-like particles, heavy neutral leptons, and meson-portal models.

Bhaskar Dutta, Debopam Goswami, Aparajitha Karthikeyan, Vishvas Pandey, Zahra Tabrizi, Adrian Thompson, Richard G. Van d (…)2026-03-30