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 scalable Heterogeneous Graph Neural Network (HGNN) that employs a multi-task learning paradigm to simultaneously perform particle vertex association and graph pruning, thereby significantly improving beauty hadron reconstruction performance and inference efficiency for complex particle collision events at the Large Hadron Collider.
This study utilizes PYTHIA 8 and EPOS-LHC models to demonstrate that particle-identified balance functions in 13 TeV proton-proton collisions exhibit distinct dependencies on event multiplicity and spherocity, revealing that while PYTHIA 8 reflects fragmentation-dominated dynamics, EPOS-LHC captures collective effects like radial flow and diffusion that mimic heavy-ion behavior, thereby offering a powerful tool to disentangle hadronization mechanisms and medium-like collectivity in small collision systems.
Using 9 fb of LHCb proton-proton collision data, this paper presents the first phase-space-binned, model-independent measurement of the CKM angle in and decays, yielding a result of that, when combined with existing integrated measurements, achieves one of the most precise determinations of to date at .
This paper presents the first results of the CASSIA sensor, a novel monolithic active pixel sensor fabricated in 180 nm CMOS technology that utilizes fully integrated internal gain layers to achieve signal amplification, enabling operation in both low-gain proportional and high-gain single-photon avalanche modes for improved timing resolution and pile-up mitigation in high-luminosity particle physics experiments.
This paper introduces QUnfold, an open-source framework that reformulates the High-Energy Physics unfolding problem as a Quadratic Unconstrained Binary Optimization (QUBO) task, enabling competitive reconstruction accuracy through both classical solvers and quantum-compatible methods like D-Wave's hybrid solver.
Using a multi-channel joint analysis of BESIII data from collisions, this study identifies the exotic charmonium-like state as a resonance with significance, while extracting its pole positions and relative branching fractions across three decay channels.
This paper demonstrates a proof-of-concept where AI agents, directed by expert physicists, independently performed a complete precision measurement of the thrust distribution in LEP ALEPH data, marking a significant step toward integrating AI into the theory-experiment loop to accelerate discoveries in fundamental physics.
This paper presents the first systematic lattice QCD study of proton- scattering across multiple pion masses and lattice spacings, yielding scattering parameters and cross sections that agree with experimental data and confirm attractive interactions critical for nuclear theory and neutron star modeling.
This paper demonstrates that different, formally equivalent resummation prescriptions for the thrust distribution in annihilation yield non-negligible numerical differences that exceed standard theoretical uncertainties, thereby necessitating more conservative error estimates in strong coupling determinations.
This paper presents the first next-to-next-to-leading order (NNLO) QCD event generation for production matched to parton showers using the MiNNLOPS method, which incorporates a novel pointwise combination of soft and high-energy two-loop amplitude approximations to provide robust, publicly available predictions for Higgs-boson decay into photons with off-shell top-quark decays.