1434 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.
Using 4.5 fb of collision data from the BESIII detector and a Transformer-based deep learning classifier, this study reports the first observation of the singly Cabibbo-suppressed decay with a statistical significance of and measures its branching fraction ratio relative to to be .
This paper presents a feasibility study demonstrating the use of Generative Adversarial Networks (GANs) to generate synthetic signal samples for rare heavy-flavour hadrons like the in ALICE Pb-Pb collisions, offering a computationally efficient alternative to traditional full simulations for enhancing reconstruction sensitivity.
This paper reports a systematic measurement of elliptic flow for strange and multi-strange hadrons in isobar collisions at GeV, revealing approximate constituent quark scaling indicative of partonic collectivity and observing a 2% deviation in flow ratios between Ru+Ru and Zr+Zr collisions that highlights differences in their nuclear structure and deformation.
This paper presents a tree-level calculation of the scattering amplitude within covariant Chiral Perturbation Theory, demonstrating that the lepton mass significantly impacts the low-energy differential cross-section and establishing a framework to determine nucleon generalized polarizabilities and low-energy constants through comparison with future experimental data.
This paper demonstrates that a low-temperature reheating scenario in the minimal Universal Extra Dimension framework can dilute the Kaluza-Klein dark matter relic abundance through entropy injection, thereby reviving previously excluded parameter regions that remain consistent with current observational and collider constraints.
This paper demonstrates that coherent perfect tunneling in a passive, lossy waveguide cascade can be achieved at an exceptional point through directional scattering degeneracy, where interference between boundary feedback loops transforms a simple zero into a second-order degeneracy to enable robust, loss-tolerant transport.
This paper introduces a new time-structured tail probability variable, , for water-Cherenkov detector arrays that significantly improves ultra-high-energy gamma-hadron discrimination by leveraging signal trace time structures, achieving a background contamination reduction of nearly a factor of five compared to existing methods.
This paper evaluates the BitNet architecture in high-energy physics applications, finding it competitive for classification tasks like quark-gluon discrimination but revealing variable performance and limitations in regression and generative modeling.
This paper proposes a method to detect sterile neutrinos by analyzing polarization observables in purely leptonic lepton decays, demonstrating that their mixing induces distinctive singularities in asymmetry parameters for masses below a specific kinematic threshold.
The MicroBooNE collaboration presents the first flux-averaged charged-current -argon cross-section measurements for final states with exactly one charged pion and no other hadrons, reporting a total cross-section of at a mean energy of 0.8 GeV and demonstrating good overall agreement with neutrino interaction generators across various differential distributions.