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 presents a hybrid classical-quantum strategy to enhance the efficiency of Hamiltonian truncation for quantum field theories by introducing an integer partition-based basis generation, symmetry-aware sparse matrix construction, and quantum Krylov diagonalization, demonstrating significant computational gains in two-dimensional scalar and models.
This paper investigates how adding a dimension-6 operator to the minimal KSVZ axion model can trigger a first-order Peccei-Quinn phase transition, producing observable gravitational wave signals and specific dark matter phenomenology within a framework supported by ultraviolet completions.
This paper demonstrates that neutrino oscillations can probe the absolute neutrino mass scale through next-to-leading-order corrections in the oscillation phase, revealing that the JUNO experiment could detect masses of a few hundred keV, thereby offering a novel and complementary method to existing mass constraints.
This paper proposes that extending modular strong-CP solutions to non-Abelian finite modular symmetries simultaneously resolves the strong CP problem by setting and generates quark mass hierarchies through a modular-anomaly condition that forces the Yukawa determinant to vanish at the cusp.
This paper introduces the Inference-driven Participant Determination (IPD) method, a Bayesian framework that utilizes charged-particle multiplicity and Monte-Carlo Glauber priors to probabilistically infer event-by-event collision geometry, thereby reducing volume fluctuations and improving the reconstruction of net-proton cumulants compared to conventional centrality classification.
Using a Chiral Anomaly Transport module within the AMPT model, this study identifies a significant Chiral Magnetic Effect signal in Au+Au collisions at GeV that aligns with STAR data, while finding the signal vanishes at 7.7 and 200 GeV due to the energy-dependent dynamics of the magnetic field and chemical freeze-out time.
This paper demonstrates that future colliders, specifically the 1 TeV ILC and 1.5 TeV CLIC, can effectively probe first-generation singlet vector-like leptons via single production channels with boosted decay signatures, achieving mass discovery reaches up to 900 GeV and 1400 GeV respectively, which surpass current hadron collider limits.
This paper investigates the simultaneous production of bosons and charmed hadrons at the LHC using next-to-leading order QCD calculations in a general-mass variable-flavor-number scheme, finding that while ratio observables effectively reduce theoretical uncertainties and reveal tension between ATLAS data and PDF sets allowing non-zero strangeness asymmetry, the processes show limited sensitivity to intrinsic charm and nuclear PDFs.
This paper proposes a nonstandard anomaly cancellation solution for the Standard Model that naturally introduces heavy neutral leptons as a minimal seesaw origin for neutrino masses, while predicting exotic quarks and leptons with specific charge assignments and masses that can satisfy experimental constraints.
Pairton is a novel, iterative graph-based framework that leverages a pairformer architecture to reconstruct short-lived particles in high-energy collisions by modeling decay relationships as a masked prediction process, achieving state-of-the-art performance on fully hadronic decays.