1387 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 novel Graph Neural Network approach to mitigate the challenges of increased beam background and irregular hadronic interactions in the Belle~II electromagnetic calorimeter by representing crystal energy depositions as sparse graphs to effectively identify and remove unwanted noise before clustering.
Using 2018 ATLAS data from ultra-peripheral Pb+Pb collisions at 5.02 TeV, this study provides the first experimental observation that nuclear parton distribution modifications vary with impact parameter, evidenced by a significant difference in jet production cross-sections between collisions with and without forward neutron emission.
This paper presents a reinterpretation of 2009 COMPASS data to search for Axion-Like Particles (ALPs) produced via the Primakoff process, deriving new exclusion limits on the ALP-photon coupling in the 0.2–600 MeV mass range by analyzing merged diphoton signatures that mimic Standard Model Compton scattering.
This paper proposes jet correlation observables to unambiguously distinguish instanton-induced processes from perturbative QCD events in proton-proton collisions at the LHC, utilizing constraints derived from 2+1 flavor QCD calculations to guide future searches at the Electron-Ion Collider.
The KOTO experiment at J-PARC successfully suppressed neutron background by a factor of while maintaining 70% signal efficiency for the rare decay search by employing deep convolutional neural networks and Fourier frequency analysis to distinguish neutrons from photons based on their distinct cluster and pulse shapes in the undoped CsI electromagnetic calorimeter.
This paper demonstrates that tensor perturbations generated during first-order cosmological phase transitions in a secluded dark sector can produce observable CMB B-mode signals comparable to inflationary predictions, potentially complicating the interpretation of future data but offering a way to distinguish the two scenarios through multi-scale measurements.
This paper investigates Higgs decays to and within the Flavor-Gauged Two Higgs Doublet Model, demonstrating that while charged Higgs loops affect both channels, is uniquely sensitive to fermion- vertex corrections that are tightly constrained by data, with future High-Luminosity LHC precision expected to significantly probe this model's parameter space.
Using quantum-correlated - decays from 7.93 fb of data collected by the BESIII experiment, this paper presents the most precise model-independent measurement of strong-phase differences for decays, which are critical inputs for reducing uncertainties in determining the $CP$-violating angle and charm mixing parameters.
This paper investigates charged lepton flavor violating top quark flavor-changing neutral current interactions at the proposed TRISTAN collider, demonstrating that an integrated luminosity of could improve current LHC constraints on scalar, vector, and tensor four-fermion contact interactions by approximately an order of magnitude.
This paper demonstrates how the Short-Baseline Near Detector (SBND) can exploit its proximity to the neutrino beam target to sample off-axis flux variations via the SBND-PRISM technique, thereby expanding physics potential and enhancing robustness against cross-section uncertainties while providing publicly available flux data and covariance matrices.