3305 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 introduces a "conformal bridge" method that utilizes the Wilson-Fisher fixed point to extend the light transform technique to non-conformal QCD, enabling the first higher-loop calculation of collider correlators like the charge-charge correlation by leveraging conformal field theory tools and recovering four-dimensional results from lower-loop data.
This paper proposes a tabletop-scale detector using an amorphous target and phonon sensing to achieve broadband sensitivity for dark photon absorption in the 50–200 meV mass range, potentially surpassing existing constraints by up to two orders of magnitude.
This paper introduces "kinetic isocurvature perturbations," a new class of primordial fluctuations arising from spatially modulated decays of heavy fields into dark matter, which evade Cosmic Microwave Background constraints by leaving early density perturbations unaffected while creating spatial variations in the matter power spectrum via changes in the free-streaming scale.
This paper investigates the slow-down of expanding bubbles during cosmological first-order phase transitions, finding that while impeding shockwaves primarily slow down the fastest walls (failing to explain gravitational wave suppression), the shrinkage of heated false vacuum droplets at the end of the transition naturally correlates with the observed suppression of gravitational waves, particularly for stronger transitions and slower deflagrations.
This paper introduces MadNIS, a framework that accelerates Next-to-Leading Order (NLO) calculations by combining fast amplitude surrogates with neural importance sampling to achieve significant speed-ups and variance reduction in electron-positron scattering processes.
This study presents a comprehensive sensitivity atlas for Big Bang Nucleosynthesis using the PRyMordial code to quantify how 14 fundamental parameters and 63 reaction rates influence primordial abundances, incorporating new LBT helium-4 data to rank theoretical uncertainties and address the deuterium tension and lithium problem.
This paper demonstrates that the autonomous AI system PhysMaster can fully automate the complex, multi-step extraction of the Collins-Soper kernel from Lattice QCD data, reducing the workflow duration from months to hours while achieving precision consistent with state-of-the-art traditional methods and stabilizing signals at large transverse separations.
This paper investigates whether three anomalous compact objects can be modeled as dark matter admixed neutron stars using a first-principles baryonic equation of state, finding that HESS J1731-347 and PSR J1231-1411 are consistent with small fermionic dark matter fractions while XTE J1814-338 is ruled out as a candidate and instead suggests a twin star scenario.
This paper analyzes pseudoscalar contributions to $Zh$ production in extended scalar sector models, finding that while a 95 GeV pseudoscalar yields negligible effects, heavier pseudoscalars (100–1000 GeV) can produce cross-sections exceeding current LHC limits, thereby constraining the parameter spaces of the Two Higgs Doublet Model and its singlet extension.
The paper introduces FERMIACC, a scaffolded reasoning model built on OpenAI agents that autonomously generates and quantitatively validates high-energy physics theory hypotheses at scale.