2585 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 and simulates a novel same-sign tetralepton signature () at the 2 TeV mode of TRISTAN to search for heavy neutral leptons and charged Higgs bosons within a low-scale seesaw model.
Using 2018 ATLAS data from ultra-peripheral Pb+Pb collisions at TeV, this paper presents the first measurement of cross-sections in nuclear collisions by statistically separating photon--pomeron, photon--photon, and peripheral photonuclear processes in non-breakup events via a template fit of rapidity gaps, while also confirming that such events select a more peripheral collision class.
Using 138 fb of CMS data at = 13 TeV, this paper presents a search for Higgs boson production in association with two vector bosons via vector boson scattering, establishing new constraints on the coupling modifier and the - plane.
Using a large sample of events collected with the BESIII detector, this study reports the first observation of the electromagnetic radiative decays and , measuring their branching fractions and revealing that the decay width challenges predictions from constituent quark and algebraic models.
DeepMET is a novel missing transverse momentum estimator developed by the CMS Collaboration that utilizes deep neural networks to assign weights to reconstructed particles, resulting in improved resolution, greater versatility across final states, and increased resilience to pileup compared to existing methods.
This paper presents a generic method using Boosted Decision Trees to multi-dimensionally reweight existing neutrino Monte Carlo simulations to match a target model, allowing for efficient reuse of legacy data without the need for new event generation.
This paper proposes a new measurement technique that combines jet charge with global event shapes (specifically 1-jettiness in DIS) to simultaneously probe quark flavor dynamics in both initial-state nucleon structure and final-state hadronization processes.
jBOT is a self-distillation pre-training method for LHC jet data that learns semantic representations by combining local particle-level and global jet-level distillation, enabling emergent class clustering that improves performance in downstream anomaly detection and classification tasks.
This paper provides a unified theoretical framework for the angular structure of energy-energy correlators (EECs) in heavy-ion collisions, demonstrating how they transition from being dominated by collective hydrodynamic flow at large angles to being controlled by hydrodynamic modes and light-ray operator product expansions at smaller angles.
This paper presents the first measurement of the angular distribution parameters, specifically the forward-backward asymmetry () and the flat term (), for the decay using LHCb data, finding results that are largely consistent with Standard Model predictions.