2551 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 introduces the petrifyML package, a tool designed to ensure the stable preservation and future reproducibility of high-energy physics machine learning algorithms by converting their configurations into industry-standard ONNX format or native Python and C++ code.
Using data from the ProtoDUNE-SP detector at CERN, this paper reports the first measurements of the total inelastic cross sections for -Ar and -Ar interactions in the sub-GeV energy regime, providing essential constraints for neutrino-argon interaction models critical to the upcoming DUNE experiment.
This paper demonstrates that assuming a Majorana nature for singlet-doublet dark matter significantly expands the viable parameter space for relic density and direct detection compared to the Dirac scenario, allowing for dark matter masses up to 1750 GeV and mixing angles up to 0.45 through the inclusion of conversion-driven processes.
Using Bayesian model comparison on approximately three years of combined ANAIS-112 and COSINE-100 data, the study finds no evidence for a dark matter-induced annual modulation signal, as the Bayes factor strongly favors a constant background model over a sinusoidal one.
Using PYTHIA 8.316 simulations, this study demonstrates that the QCD analogue of the inverse Compton effect in quark-gluon scattering increasingly dominates secondary particle production in proton-proton collisions as energy rises from 30 GeV to 14 TeV, particularly influencing transverse momentum and central pseudorapidity distributions due to enhanced small-x gluon interactions.
This paper proposes that the dynamical inverse seesaw mechanism, which explains light neutrino masses through a low-scale lepton number-violating term, can be probed via low-frequency stochastic gravitational waves detected by pulsar timing arrays, offering a unique window into parameter space with small active-sterile mixing that is inaccessible to conventional particle physics experiments.
This paper investigates how collider and non-collider probes can constrain the reheating temperature, dark matter mass, and interaction scale of a scenario where dark matter transitions from WIMP to FIMP production via p-wave suppressed interactions, demonstrating that collider experiments are uniquely powerful in constraining derivative operators that are weakly limited by astrophysical observations.
Using 138 fb of 13 TeV proton-proton collision data from the CMS experiment, this study searches for exotic Higgs boson decays into pairs of light scalar particles (0.4–2.0 GeV) that decay into collimated muon and hadron pairs, setting upper limits on the branching fraction at the level for proper decay lengths up to 1 mm.
Using QCD sum rules, this study investigates the hadronic tensor molecule , calculating its mass and decay width to propose it as a viable candidate for the experimentally observed resonance .
This paper analyzes the sensitivity of current and future collider observables to individual top-quark SMEFT operators using data from the Tevatron, LEP, and LHC Run 2, alongside HL-LHC and future lepton collider projections, to identify the most constraining measurements and highlight expected improvements in sensitivity.