5589 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 pragmatically constrains the initial states of relic gravitons at the moment their wavelengths cross the comoving Hubble radius, concluding that while non-vacuum states are marginally permitted for low-frequency modes, the intermediate and high-frequency spectrum (kHz to THz) is dominated by vacuum-produced gravitons with negligible initial state contributions.
This paper proposes that a supercooled first-order phase transition in a hidden sector with spontaneously broken gauge symmetry can generate a gravitational wave background strong enough to explain recent Pulsar Timing Array observations while remaining consistent with Big Bang Nucleosynthesis constraints.
This paper establishes the primary HEFT (pHEFT) as a precision benchmark framework for matching ultraviolet-complete scalar extensions, such as the Real Higgs Triplet Model, by utilizing inverse squared heavy masses as expansion parameters to preserve maximal UV information and systematically derive alternative HEFT formulations, including the first derivation of RHTM operators involving fermions.
This paper reviews the historical development and key physical concepts of quantum entanglement and Bell inequalities, highlighting C. S. Wu's early contributions and the achievements recognized by the 2022 Nobel Prize in Physics.
This paper demonstrates that non-invertible selection rules derived from the Tambara–Yamagami fusion algebra can naturally enforce the absence of tree-level contributions while enabling a dominant one-loop seesaw mechanism for neutrino mass generation and simultaneously stabilizing dark matter candidates.
This paper investigates the stochastic gravitational wave background generated by a first-order phase transition ending a kination-dominated epoch in the Kination-Induced Big Bang scenario, demonstrating that such a mechanism can dynamically induce metastability and produce a signal spanning nHz to MHz frequencies that is consistent with Pulsar Timing Array observations and testable by future interferometers.
By analyzing full-sky gamma-ray predictions from local large-scale structure using constrained N-body simulations and comparing them with Fermi-LAT observations, this study establishes the tightest constraints to date on velocity-dependent p- and d-wave dark matter annihilation, finding no evidence for such signals and deriving limits significantly stronger than those from dwarf spheroidal galaxies.
This paper reports the first high-significance (>5σ) experimental observation of strong-field radiation reaction where quantum effects are substantial, providing quantitative evidence that favors quantum-continuous and quantum-stochastic models over the classical model through a novel Bayesian analysis framework.
This paper introduces PDFxTMDLib, a modern, high-performance C++ library that overcomes the customization and uncertainty analysis limitations of existing tools like LHAPDF and TMDLib by providing a flexible framework for both collinear and transverse momentum dependent parton distribution functions, which is validated through integration with the PYTHIA event generator and comparative studies.
This paper demonstrates that likelihood-free Simulation-Based Inference, particularly the Neural Posterior Estimation method, offers a computationally efficient and accurate alternative to traditional MCMC for exploring high-dimensional Beyond the Standard Model parameter spaces, successfully inferring posterior distributions for both 5-parameter and 9-parameter pMSSM scenarios including dark matter constraints.