5500 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 demonstrates for the first time that neural simulation-based inference (NSBI) can effectively constrain proton parton distribution functions using high-dimensional, unbinned LHC data, achieving significantly improved precision over traditional binned analyses by fully exploiting statistical power and reducing reliance on coarse uncertainty approximations.
This paper presents the first lattice QCD study of ground-state spin- heavy baryons containing charm and bottom quarks using fully relativistic valence quarks on physical HISQ ensembles.
This paper utilizes precision measurements of top-associated photon production ( and ) from the LHC to derive complementary constraints on the electromagnetic and chromomagnetic dipole couplings of vector-like top partners within an effective field theory framework, demonstrating that such observables effectively probe radiative decay scenarios where traditional resonance searches may be less sensitive.
This paper extends the Operator Product Expansion (OPE) algorithm to scalar-QED theory by computing the four-loop anomalous dimension of the fixed-charge operator , along with beta functions and other anomalous dimensions, while introducing a novel loop-integrand construction method to validate the OPE approach for higher-loop renormalization beyond pure scalar theories.
This study presents a comprehensive analysis correlating the highest-energy neutrino event KM3-230213A with gamma-ray bursts by explicitly accounting for angular uncertainties and computing Lorentz invariance violation scales to identify a broader set of potential associations.
This paper presents a novel technique for next-to-leading order accurate simulation of that incorporates finite width effects beyond the Breit-Wigner approximation in resonance- and width-aware parton shower evolution and NLO matching, offering a publicly available tool for future electron-positron collider studies.
This paper employs a dynamical heavy diquark model based on the Bethe-Salpeter equation to calculate the masses, wave functions, magnetic moments, and radiative decay widths of doubly- and triply-heavy baryons, comparing these results with existing data and predicting properties for unobserved triply heavy baryons.
This paper investigates three types of new physics resonances that couple to Standard Model quarks through direct top-quark flavor-changing interactions, identifying the relevant SMEFT operators at the electroweak scale and analyzing their phenomenological implications.
This paper develops a systematic worldline effective field theory framework to compute gravitational Sommerfeld factors for binary inspirals with tidal effects, deriving closed-form expressions and analytically solving for the magnitude and phase of the factor up to while establishing a new renormalization group equation for radiative multipole moments to improve waveform resummation.
This paper presents a global Bayesian analysis of unpolarized quark transverse-momentum-dependent parton distribution functions using Drell-Yan data at and accuracy, leveraging AI-driven functional form selection and machine-learning emulators to enable efficient Markov Chain Monte Carlo sampling and quantify uncertainties.