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.
This paper presents the first implementation of a real-time Graph Neural Network on an FPGA for the Belle II electromagnetic calorimeter trigger, which achieves 8 MHz throughput with 3.168 μs latency while significantly improving position resolution, cluster purity, and efficiency compared to the baseline algorithm.
This paper evaluates the detectability of the intense neutrino burst generated by the stellar helium flash in low-mass stars, concluding that while next-generation observatories like Jinping could detect such events within approximately 3 parsecs, the absence of nearby candidate stars currently makes asteroseismology the primary method for studying this phenomenon.
This document updates the U.S. community's contributions to the European Strategy for Particle Physics Update as of April 1, 2025, highlighting key developments such as a new National Academies long-term strategy report and the formal establishment of a U.S. Muon Collider Collaboration.
This paper presents a new DeepSets-based deep neural network algorithm that significantly improves the inclusive flavour tagging performance for neutral and mesons at LHCb, achieving a 35% and 20% gain in tagging power respectively over existing methods to enhance precision measurements of $CP$ violation and mixing.
The 2026 update for the COHERENT experiment outlines its strategy to achieve percent-level precision in measuring coherent elastic neutrino-nucleus scattering and other neutrino-nucleus cross sections by scaling up detector masses, lowering thresholds, and utilizing diverse nuclear targets at the Spallation Neutron Source to test the Standard Model and support future supernova neutrino detection efforts.
This paper computes charm and strange meson fragmentation functions by deriving and solving a set of twenty-five coupled jet equations based on Poincaré covariant Bethe-Salpeter wave functions, thereby providing a consistent description of quark hadronization across both light and heavy sectors.
This paper demonstrates the first viable, ultra-fast machine learning application on radiation-hard FPGAs by developing a lightweight autoencoder for the PicoCal calorimeter and extending the hls4ml library with a new backend to synthesize the model for Microchip PolarFire devices, achieving a 25 ns latency with minimal resource usage.
This paper investigates neural scaling laws for boosted jet classification using the JetClass dataset, demonstrating that increasing compute reliably drives performance toward asymptotic limits while revealing how data repetition, input features, and particle multiplicity influence scaling efficiency and effective dataset size.
This paper proposes a quantum-encoded data analysis methodology using parity observables on an 8-qubit processor to compress and recover neutrino telescope event information with 84% fidelity, enabling the classification of electron- and muon-neutrino events to overcome the limitations of traditional triggers and the "street light effect" in particle physics.
This paper proposes and analyzes two minimal, ultraviolet-complete tri-hypercharge models that explain Standard Model fermion masses and mixings through three correlated physical scales, predicting that the lightest boson in these theories is discoverable via dilepton searches at LHC Run 3.