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.

⚛️ phenomenology

Agentic AI -- Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data

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.

Anthony Badea, Yi Chen, Yen-Jie Lee2026-03-09
⚛️ phenomenology

A Lattice QCD study of p−Λp-\Lambda scattering in continuum and chiral limits

This paper presents the first systematic lattice QCD study of I=1/2I=1/2 proton-Λ\Lambda 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.

Hang Liu, Liuming Liu, Jin-Xin Tan, Wei Wang, Haobo Yan, Qian-Teng Zhu2026-03-09
⚛️ phenomenology

Next-to-next-to-leading order event generation for ttˉHt\bar{t}H production with approximate two-loop amplitude

This paper presents the first next-to-next-to-leading order (NNLO) QCD event generation for ttˉHt\bar{t}H 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.

Christian Biello, Chiara Savoini, Chiara Signorile-Signorile, Marius Wiesemann2026-03-09
⚛️ high-energy experiments

Transformer-Based Pulse Shape Discrimination in HPGe Detectors with Masked Autoencoder Pre-training

This paper demonstrates that transformer-based models, particularly when enhanced by masked autoencoder pre-training, outperform traditional gradient-boosted decision trees in pulse-shape discrimination and energy regression for HPGe detectors by leveraging full waveform data and significantly reducing the need for labeled training samples.

Marta Babicz, Saúl Alonso-Monsalve, Alain Fauquex, Laura Baudis2026-03-09
⚛️ phenomenology

Latin American HECAP Physics Briefing Book 2025

This paper presents the updated 2025 Physics Briefing Book for the Latin American Strategy Forum for Research Infrastructure in High Energy, Cosmology, and Astroparticle Physics (LASF4RI-HECAP), which synthesizes 46 community white papers and symposium discussions to establish a long-term strategic roadmap across seven key scientific and technical working groups.

Mario A. Acero (U. del Atlántico - Colombia), Alexis A. Aguilar-Arevalo (UNAM - México), Belén Andrada (CNEA/CONICET/UNS (…)2026-03-09
⚛️ high-energy experiments

Modern jet flavour tagging in hadronic Z decays with archived ALEPH data

This paper presents a reanalysis of archived ALEPH LEP data using modern deep learning-based jet flavour tagging techniques, which significantly improve the separation of b-, c-, and s-quark jets compared to legacy algorithms and demonstrate successful data calibration, thereby enabling more precise electroweak measurements and guiding future collider detector development.

Matteo M. Defranchis, Jacopo Fanini, Apranik Fatehi, Gerardo Ganis, Taj Gillin, Loukas Gouskos, Luka Lambrecht, Michele (…)2026-03-09
⚛️ phenomenology

Current status of the light neutralino thermal dark matter in the phenomenological MSSM

This paper reaffirms the robustness of strong experimental constraints on light neutralino thermal dark matter within the phenomenological MSSM, explores the impact of light staus and non-standard cosmology, and proposes machine learning-optimized benchmarks for future LHC Run-3 searches.

Rahool Kumar Barman, Genevieve Bélanger, Biplob Bhattacherjee, Rohini Godbole, Rhitaja Sengupta2026-03-06