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

CPCP violation in singly Cabibbo suppressed Dπa0(980)D\to \pi a_0(980) decays

This contribution suggests that significant long-range rescattering effects, particularly the process DKKa0πD\to K^*K\to a_0\pi, explain the large experimental branching ratios in singly Cabibbo-suppressed Dπa0(980)D\to \pi a_0(980) decays and naturally predict direct CPCP asymmetries at the level of 10310^{-3}, thereby establishing these decays as a promising new approach for investigating CPCP violation.

Yu-Kuo Hsiao, Shu-Ting Cai, Yan-Li Wang2026-04-29
⚛️ high-energy experiments

Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane

This contribution evaluates and compares perturbation-based, Shapley-value-based, and gradient-based interpretability methods adapted for the representation of the Lund-Jet-Plane and demonstrates that these techniques successfully correlate neural network predictions with classical QCD observables while revealing pronounced shifts in focus between perturbative and non-perturbative regimes in jet tagging.

Pahal D. Patel, Sanmay Ganguly2026-04-29
⚛️ high-energy experiments

Search for light pseudoscalar boson pairs produced from Higgs boson decays using the 4τ\tau and 2μ\mu2τ\tau final states in proton-proton collisions at s\sqrt{s} = 13 TeV

Using 138 fb⁻¹ of CMS data from 13 TeV proton-proton collisions, this study searched for light pseudoscalar boson pairs produced from Higgs boson decays in the 4τ\tau and 2μ\mu2τ\tau channels, finding no excess above Standard Model expectations and setting upper limits on the branching fraction, particularly within the context of 2HD+S models.

CMS Collaboration2026-04-28
⚛️ nuclear experiments

Jet fragmentation function and groomed substructure of bottom quark jets in proton-proton collisions at 5.02 TeV

This paper presents the first measurement of bottom quark jet substructure and fragmentation functions in 5.02 TeV proton-proton collisions using a novel algorithm to cluster charged b-hadron decay daughters, providing experimental evidence for the dead-cone effect through the observation of suppressed emissions at small radii compared to inclusive jets.

CMS Collaboration2026-04-28
⚛️ lattice

Hamiltonian formulation of the 1+11+1-dimensional ϕ4ϕ^4 theory in a momentum-space Daubechies wavelet basis

This paper applies a momentum-space Daubechies wavelet basis within the Hamiltonian framework to investigate nonperturbative dynamics in 1+11+1-dimensional ϕ4\phi^4 theory, successfully reproducing the strong-coupling phase transition and demonstrating systematic convergence of the critical coupling as momentum resolution increases.

Mrinmoy Basak, Debsubhra Chakraborty, Nilmani Mathur, Raghunath Ratabole2026-04-28
⚛️ high-energy experiments

Enabling users to work sustainably on shared institute computing resources

The VISPA project promotes sustainable computing on a mid-scale physics cluster by implementing user-centric tools—such as per-job energy monitoring, "green-window" scheduling based on renewable energy availability, and voluntary carbon footprint reporting—to foster environmental awareness and reduce emissions through behavioral change.

Niclas Eich, Johannes Erdmann, Martin Erdmann, Benjamin Fischer, Paul Gilles, Tim Hauptreif, Jan Kelleter2026-04-28
⚛️ high-energy experiments

Passage of particles through matter and the effective straggling-function: High-fidelity accelerated simulation via Physics-Informed Machine Learning

The paper introduces PHIN-GAN, a physics-informed generative adversarial network that utilizes analytical probability density functions of the Landau straggling function to provide high-fidelity, scalable, and computationally efficient simulations of particle-matter interactions compared to traditional methods like GEANT4.

Oleksandr Borysov, Rotem Dover, Eilam Gross, Nilotpal Kakati, Noam Tal Hod2026-04-28