1442 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 a global analysis combining KamLAND data with Daya Bay's independently measured fission antineutrino spectra, revealing that using these empirical spectra instead of the Huber-Müller model reduces the tension between KamLAND's and JUNO's measurements of solar neutrino oscillation parameters by lowering the best-fit values of and .
Using a large sample of events collected by the BESIII detector, this study reports the first observation of the decay with branching fractions determined under different interference scenarios, while setting an upper limit on the unobserved decay .
This paper describes the development and successful six-month operation of an EPICS-based low-temperature monitoring and alarm system for the Taishan Antineutrino Observatory, which utilizes PT100 sensors and multi-level thresholds to ensure the safe and stable operation of the detector by tracking liquid scintillator temperatures.
This paper introduces a wire-by-wire tracking efficiency diagnostic for the Belle~II Central Drift Chamber, which extrapolates reference tracks to individual wires to identify localized tracking failures that remain invisible to conventional channel-level monitoring.
This paper demonstrates that integrating quantum error correction with logical GHZ entanglement in CMOS spin qubit arrays can effectively mitigate longitudinal dephasing, thereby restoring entanglement-enhanced sensitivity and achieving order-of-magnitude improvements in detecting axion-electron coupling for dark matter searches.
This paper presents a lightweight conditional Generative Adversarial Network (cGAN) that significantly accelerates the simulation of FARICH detector responses by generating realistic photon hit samples conditioned on particle tracks and momentum, outperforming traditional Monte-Carlo methods in speed while maintaining accuracy.
This paper summarizes recent LHCb results on Flavour Changing Neutral Current decays, including a legacy measurement of using 8.4 fb of Run 1 and 2 data, to search for New Physics and investigate long-standing tensions with Standard Model predictions in transitions.
This paper presents updated experimental constraints on the gravitational inverse-square law at short ranges, offering a consistent formalism to compare diverse tabletop and high-energy collider results with theoretical extensions of general relativity, including extra-dimensional models.
This paper proposes a significantly enhanced detection scheme for meV-scale QCD axions and dark photons using highly excited cyclotron states of a trapped electron within an open-endcap trap, achieving background-free sensitivity to the predicted post-inflationary QCD axion mass range (0.1–2.3 meV) and dark photon kinetic mixing parameters as low as through optimized experimental parameters and dielectric-enhanced cavities.
This paper proposes a hybrid neural simulation-based inference approach to constrain the Higgs trilinear self-coupling and other SMEFT operators using off-shell Higgs production at the High-Luminosity LHC, achieving near-theoretical-optimal sensitivity by combining matrix-element-enhanced training with classification-based background estimation.