1404 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 outlines the analysis techniques, background composition, and rejection procedures employed by the PADME experiment at Laboratori Nationali di Frascati to search for the Dark Photon via positron-electron annihilation using the missing mass technique.
This paper presents double-differential inclusive jet cross sections measured by the STAR detector in proton-proton collisions at and $510$ GeV, providing new constraints on the poorly known gluon parton distribution function in the proton through comparisons with next-to-next-to-leading order perturbative QCD calculations.
This paper investigates the potential of multi-kiloton liquid scintillator detectors to measure the CP-violating phase in atmospheric neutrino oscillations by calculating expected event rates and distributions across various sites and detector configurations, ultimately estimating sensitivity through a Poisson likelihood analysis.
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.
This paper introduces a differentiable conditional denoising-diffusion surrogate for electromagnetic calorimeter simulations that achieves high-fidelity energy-deposition maps with minimal retraining via Low-Rank Adaptation and provides accurate gradients for gradient-based detector design optimization.
This paper benchmarks three exclusive nuclear ground-state shell models implemented in the NEUT neutrino event generator against recent JSNS 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.
This paper presents a novel hybrid model for semileptonic meson decays that utilizes an optimal transport algorithm to seamlessly merge resonant and non-resonant components, thereby eliminating unphysical features like discontinuities and negative yields found in current simulation methods.
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.
This paper proposes a signal-aware latent space construction using supervised contrastive learning to overcome the curse of dimensionality in particle physics, enabling high-fidelity weakly supervised anomaly detection that significantly improves discovery sensitivity for both trained and unseen Beyond the Standard Model signals.
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.