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 evaluates the LHC's potential to detect the scalar radial excitation in composite and twin Higgs models, establishing current mass bounds of 0.93–1.13 TeV from Run 2 data and projecting HL-LHC sensitivities up to 2.2 TeV, with the Higgs pair decay channel identified as the most promising discovery mode.
This paper employs a symmetry-preserving vector-vector contact interaction to calculate the four kaon transverse momentum dependent parton distribution functions (TMDs), offering insights into the roles of emergent hadron mass, Higgs-boson coupling effects on strange quark mass, gauge link models regarding positivity constraints, and scale-evolution impacts on the Boer-Mulders function.
This paper proposes a highly sensitive search for charged lepton flavor violation via a unique same-sign dimuon signature () mediated by axionlike particles at electron-photon colliders, which offers a background-free environment capable of probing couplings one to two orders of magnitude beyond current limits.
This paper traces the historical development of the atomic bomb and examines the profound moral dilemmas faced by scientists regarding its use against Japan, aiming to contribute to future discourse on the ethical guidance of scientific research.
Using proton-proton collision data from the ATLAS experiment at 13 and 13.6 TeV, this study reports the first measurement of quantum entanglement between spins in pairs of Z bosons produced from Higgs boson decays, providing strong evidence (4.7σ significance) for entangled massive bosons at the electroweak scale.
This paper proposes a discovery-grade framework for detecting sub-MeV dark matter by searching for correlated "satellite-line combs"—multiple weak -ray lines shifted by a common energy offset below known neutron-capture transitions—using high-resolution HPGe detectors to suppress nuclear and instrumental backgrounds.
PQuantML is an open-source, hardware-aware library that streamlines end-to-end neural network compression through joint or individual pruning and fixed-point quantization, demonstrating significant parameter and bit-width reductions with maintained accuracy on real-time LHC jet tagging tasks compared to existing tools like QKeras and HGQ.
This paper presents CaloScore v2, an improved diffusion-based model for fast calorimeter shower simulation that utilizes progressive distillation to achieve high-fidelity sample generation with a single function evaluation, thereby overcoming the computational bottlenecks of traditional diffusion processes.
This paper introduces SBUnfold, a novel generative unfolding method leveraging Schrödinger Bridges and diffusion models to combine the strengths of discriminative and generative approaches, enabling efficient, high-dimensional cross-section measurements without relying on known probability densities.
This paper demonstrates how a new Foundation Model for hadronic jets addresses three critical challenges in collider physics—reducing computational costs for reconstruction, enabling comprehensive uncertainty quantification, and facilitating model-agnostic new physics searches—thereby transitioning jet-based Foundation Models from proof-of-concept studies to practical tools for researchers.