2160 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 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.
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.
The paper introduces "OmniLearn," a jet-physics foundation model that leverages a representation learned from a specific multiclass generation and classification task to simultaneously enhance the accuracy, precision, and speed of diverse downstream jet physics tasks across different datasets, collision systems, and analysis goals.
This paper proposes a holistic approach and Advanced Color Singlet Identification (ACSI) using state-of-the-art AI to simultaneously classify physics events and associate final-state particles with parent bosons, significantly improving the accuracy of Higgs boson decay measurements at future high-energy colliders.
This paper derives updated constraints on flavor-violating boson couplings to quarks, demonstrating that low-energy flavor experiments currently provide significantly tighter bounds (ranging from to ) than existing collider searches and presenting future sensitivity projections.
This paper proposes an extended inelastic Higgs-portal complex singlet model that simultaneously explains dark matter, the Galactic Center gamma-ray excess, and the baryon asymmetry of the universe through a two-step electroweak phase transition featuring spontaneous CP violation, while predicting gravitational wave signals detectable by future space-based observatories.
Using a dataset of 121.3 million decays collected by the BaBar detector, this study presents the first measurements of angular distributions and improved branching fractions for transitions while finding no evidence for the decay mode.
This paper reports the successful characterization of an FBK NUV-HD-cryo silicon photomultiplier operated at 9.4 mK within a dilution refrigerator, demonstrating its viability for detecting cosmic-ray muons in low-background dark matter experiments like QUEST-DMC.