3393 papers
Hep-Ph explores the fundamental forces that govern how particles interact and behave at the smallest scales imaginable. This field bridges the gap between theoretical predictions and experimental reality, helping scientists understand the building blocks of our universe without getting lost in complex mathematics. Whether investigating the Higgs boson or searching for new physics beyond current models, these studies push the boundaries of human knowledge about matter and energy.
At Gist.Science, we process every new preprint in this category as soon as it appears on arXiv. We strip away the dense jargon to offer both accessible plain-language explanations and detailed technical summaries, ensuring that groundbreaking research is understandable to everyone from students to seasoned experts. Below are the latest papers in this dynamic field, ready for you to explore with clarity and depth.
This paper presents LHEReader, a program that simplifies the conversion of Les Houches Event files into ROOT format, demonstrating its performance and utility through various particle physics simulations and analyses.
This paper derives the covariant generalization of the Frank-Tamm formula for Cherenkov radiation and the associated orthogonal four-force friction, proposing its application to explain soft photon excesses in relativistic hadron collisions.
This paper calculates transition form factors using QCD light-cone sum rules with -meson distribution amplitudes to derive lower limits on the branching fraction required for -mesogenesis, concluding that experimental sensitivity must reach the to level to decisively probe this invisible decay mode.
Using first-principles lattice simulations of SU(3) Yang-Mills theory in Rindler spacetime, this study demonstrates that weak acceleration induces a spatially inhomogeneous confinement-deconfinement phase transition where distinct phases coexist, with a phase boundary consistent with theoretical predictions and a critical temperature matching that of non-accelerated gluodynamics.
This paper investigates the phenomenology of scalar leptoquarks coupled to right-handed Majorana neutrinos at the High-Luminosity LHC, demonstrating that the distinctive same-sign dimuon and multi-jet signature allows for the exploration of lepton-number violating processes and extends the discovery reach for multi-TeV leptoquarks beyond current constraints through a comprehensive analysis of both pair and single production modes.
This paper proves that scale-invariant one-loop corrections to superhorizon curvature perturbations from small-scale scalar modes are absent in general inflationary scenarios, including transient ultra-slow-roll, due to dilatation symmetry and explicit one-loop calculations within an in-in effective field theory framework.
This paper demonstrates that upcoming low-threshold coherent elastic neutrino-nucleus scattering experiments at major spallation sources (ESS, J-PARC, and CSNS) will significantly probe previously unexplored parameter space for sub-GeV thermal dark matter produced via neutral pion decays and mediated by vector portals.
This paper reframes Quantum Neural Network design from state reachability to learnability by introducing geometric design principles and the almost Complete Local Selectivity (aCLS) criterion, demonstrating that architectures requiring joint dependence on data and trainable weights enable adaptive feature learning and outperform traditional schemes with greater efficiency.
This paper proposes that relic neutrinos from the Big Bang can be detected via parametric fluorescence, a coherent scattering process in atomic or molecular systems where a massive neutrino decays into a lighter neutrino and a signal photon, offering a promising detection method with event rates potentially reaching one per year in optimized target volumes.
This paper employs Bayesian model selection to optimize the energy dependence of parameters in a (3+1)-dimensional hybrid framework for relativistic heavy-ion collisions, subsequently using the resulting posterior distributions to predict various flow observables and quantify systematic uncertainties across different collision systems.