5257 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 establishes the perturbative stability of the fuzzy-sphere black-hole horizon in large- matrix quantum mechanics by demonstrating that quantum corrections stabilize classically unstable modes through a non-negative Hessian structure, with a critical crossover regime at where quantum and classical effects become comparable.
This paper investigates cosmological signatures of the Next-to-Minimal Two-Higgs-Doublet Model in both conformal and non-conformal realizations, demonstrating that while both scenarios can generate observable gravitational waves from a first-order electroweak phase transition, they occupy distinct regions of the scalar mass spectrum and exhibit different patterns in Higgs-pair production rates, thereby offering a pathway to discriminate between the two models through combined cosmological and collider data.
This paper presents a new recursive algorithm implemented in the OpenLoops framework to reduce arbitrary two-loop tensor integrals to scalar integrals, marking a significant step toward fully automated next-to-next-to-leading order calculations for high-precision collider physics.
This chapter outlines the contemporary theoretical understanding of exotic hadrons containing essential gluonic excitations, specifically glueballs and hybrids, while discussing the challenges involved in definitively identifying these states within the experimental hadron spectrum.
This paper employs QCD sum rules to investigate hidden- and open-strange pentaquark molecular configurations, finding no bound states in the sector but identifying a near-threshold bound state around 2.2 GeV in the sector and proposing specific spin-parity assignments for several poorly established strange baryons.
This paper demonstrates that the cosmological role of the heaviest decoupled right-handed neutrino in the minimal type-I seesaw model is significant, as its long-lived presence can substantially delay charged lepton Yukawa equilibration, thereby altering flavor regimes in thermal leptogenesis and impacting broader cosmic evolution including dark matter production and gravitational wave spectra.
This paper proposes a Minimal Supersymmetric Standard Model framework utilizing non-invertible selection rules derived from gauging the outer automorphism of a discrete symmetry to simultaneously generate realistic fermion mass textures and suppress flavor-changing neutral currents while maintaining stability under renormalization group evolution.
This paper addresses the critical challenge of model misspecification in machine learning applications for physics, arguing that robust analysis requires an iterative cycle of complementary diagnostics and model updates, underpinned by a mindset that anticipates and accommodates unforeseen errors to distinguish between new discoveries and analytical biases.
This paper demonstrates that sizable axion isocurvature perturbations can survive the scaling evolution and eventual annihilation of axion domain walls, as the biased vacuum energy released during collapse inherits and transfers superhorizon inflationary correlations to the axion dark matter density.
The paper introduces ORCA, a two-stage framework combining supervised contrastive learning with autoencoders to achieve both improved sensitivity and interpretability in collider anomaly detection by mapping events into an embedding space where anomalous samples can be quantitatively attributed to known physics processes.