1493 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 reports the first experimental observation of dressed states of proton spins in water using a strong off-resonant magnetic field, demonstrating multiple spin-state transitions that align with the quantum Rabi model beyond the rotating-wave approximation and extending precision spin manipulation capabilities in nuclear magnetic resonance.
This paper details the design, construction, and performance of the Super Fine-Grained Detector (SuperFGD), a novel segmented plastic scintillator installed in the T2K experiment's upgraded ND280, which utilizes 3D tracking, high light yield, and sub-nanosecond timing to significantly improve particle identification and enable the first reconstruction of neutron kinetic energy in a neutrino experiment.
Using the full ATLAS Run 2 dataset of 140 fb at 13 TeV, this study reinterprets thirteen supersymmetry searches to set comprehensive 95% confidence level mass limits on gluinos, top squarks, tau-sleptons, and charginos/neutralinos across a broad spectrum of R-parity-violating coupling strengths, thereby bridging the gap between prompt and long-lived particle signatures.
This paper investigates whether a massive sterile neutrino could explain the discrepancy between -meson and -baryon decay anomalies by revisiting the semileptonic sum rule, concluding that the induced effects are too small to resolve the tension and thus the sum rule remains a robust consistency check for experimental data.
This paper presents the design and room-temperature operational results of a spark chamber prototype equipped with a flash lamp, intended to generate vacuum ultraviolet light for testing precision sensors used in noble liquid detectors for dark matter and neutrino physics.
This paper proposes migrating LEP data to the standardized EDM4hep format to mitigate long-term data loss risks, enhance FAIRness, and leverage the dataset as a crucial benchmark for the future FCC-ee physics program, a strategy validated by a successful proof-of-concept migration of ALEPH data.
This paper proposes a model utilizing vector-like quarks and scalar messengers with hierarchical vacuum expectation values to explain the quark mass hierarchy and generate the CKM matrix independently of fermion masses, thereby addressing the Standard Model's inability to account for flavor structure.
This paper introduces the "Kink Finder," a specialized track-finding algorithm for the Belle II experiment that significantly outperforms standard methods by achieving a 40% reconstruction efficiency for in-flight particle decays and scattering, while also improving track parameter resolution and reducing misidentification rates.
This paper demonstrates that while the Krauss-Nasri-Trodden (KNT) model can satisfy low-energy experimental constraints, a significant portion of its viable parameter space is ruled out by vacuum stability conditions when renormalization group effects are considered, leaving most of the remaining region testable through future charged lepton flavor violating experiments.
This paper summarizes recent advancements in using constituent-based machine learning architectures, such as graph neural networks and transformers, to classify hadronic final states in the ATLAS Experiment, detailing their performance on simulated and real data while outlining future directions for data-driven and model-independent tagging strategies.