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 utilizes a semi-analytical model of galaxy and supermassive black hole evolution within the CDM paradigm to demonstrate that the observed stellar mass–black hole mass relation at high redshifts disfavours fuzzy dark matter fields with masses below eV and warm dark matter particles with masses below 7.2 keV at the 95% confidence level.
Using dispersion theory to account for strong pion-pion final-state interactions, this study demonstrates that the substructure near the threshold in decays can be reproduced without invoking an extra resonance, attributing the observed dip primarily to a helicity-flip amplitude rather than the virtual exchange of the state.
Using 138 fb of proton-proton collision data at 13 TeV collected by the CMS detector, this paper presents three "mono-X" searches for invisible new physics in pencil-jet, mono-photon, and mono-top final states, finding no significant deviations from Standard Model predictions and setting stringent exclusion limits on dark matter and large extra dimension models.
This paper proposes that a minimal dark scalar with a mass of approximately 9.40 GeV, which shares high- fragmentation scaling with NRQCD color-octet production, can simultaneously explain the anomalous high- plateau in nuclear modification factors, the vanishing elliptic flow, and the quarkonium polarization puzzle in heavy-ion collisions while evading historical low- constraints.
This paper employs both machine learning techniques and an extended analytical mass formula to predict the mass spectra of fully-heavy baryons and exotic pentaquarks, offering complementary insights that align with existing experimental data and guide future searches for unobserved states.
The paper proposes "Unified Flavor," a framework where hierarchical Yukawa couplings and CP violation emerge from TeV-scale vectorlike fermion chains on a -lattice governed by a single flavon, successfully reproducing quark and lepton mass spectra while simultaneously addressing flavor constraints, strong CP, and offering testable predictions for future experiments.
This paper reports the first measurement of the cosmic muon flux at the Stawell Underground Physics Laboratory using eight plastic scintillator panels, yielding a value of (6.33 ± 0.04_stat ± 0.35_sys) × 10⁻⁸ s⁻¹ cm⁻² that aligns well with simulations and features significantly reduced uncertainty compared to modeling.
This paper proposes that the Dark Technicolour paradigm, utilizing the Extended Most Attractive Channel hypothesis across three confining gauge sectors, revitalizes conventional Technicolour dynamics to generate Standard Model fermion masses and resolve the Flavor Problem through a hierarchical structure of multifermion condensates.
Using 137 fb⁻¹ of 13 TeV proton-proton collision data from the ATLAS detector, this study searches for long-lived particles via displaced vertices and missing transverse momentum, finding no significant excess over Standard Model backgrounds and setting 95% confidence-level limits on four specific beyond-the-Standard Model scenarios.
This paper introduces PoLAr-MAE, a self-supervised masked point modeling framework for Liquid Argon Time Projection Chamber (LArTPC) data that learns physically meaningful trajectory representations from unlabeled events, achieving state-of-the-art segmentation performance with minimal labeled data and demonstrating the potential for a universal foundation model in particle physics.