5626 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 employs the SMEFT framework to demonstrate that the beam polarizations and high center-of-mass energies of the ILC and CLIC enable precise probing of the chirality structure of lepton flavor violating processes, offering sensitivity to four-fermion operators that rivals or surpasses projections from Belle-II tau decay studies.
This paper demonstrates that clipping Effective Field Theory (EFT) simulations at the new physics scale via an invariant mass cut () is insufficient to guarantee EFT validity across different observables and operator orders, while also highlighting the risks of introducing model-dependent form factors and proposing alternative transverse mass cuts for more robust sensitivity studies.
This study utilizes DESI DR2 data to constrain a field-theoretic model where interacting spin-zero fields represent dark matter and dark energy, demonstrating how varying interaction strengths can address the Hubble tension and explain the dynamical nature of dark energy.
The paper proposes a new "Derivative Portal Dark Matter" model where a massive mediator couples to the Standard Model via derivative interactions, allowing the theory to naturally satisfy relic density constraints while evading limits from direct detection, indirect detection, and collider searches.
This paper investigates the stochastic oscillations between axion-like particles emitted by ultra-light primordial black holes and photons within primordial magnetic fields, analyzing their probability distributions and potential impacts on the cosmic microwave, X-ray, and gamma-ray backgrounds.
This paper investigates di-Higgs production and Higgs trilinear coupling modifications within a Standard Model extended by a real scalar singlet, identifying benchmark points in the multi-TeV resonance regime that remain viable under current LHC constraints and offer distinct discovery potential for future colliders like the HL-LHC, CEPC, FCC-ee, and ILC.
This paper introduces Quantum Rationale-Aware Graph Contrastive Learning (QRGCL), a resource-efficient framework that integrates a quantum rationale generator to achieve competitive quark-gluon jet discrimination performance with a compact 45-parameter architecture, effectively addressing challenges in feature extraction and limited labeled data in high-energy physics.
This paper proposes a gauged extension of the Standard Model that utilizes the type-III seesaw mechanism to generate neutrino masses while employing anomaly-canceling chiral fermions as dark matter candidates, with a comprehensive analysis of their phenomenological signatures across cosmology, direct/indirect detection, collider physics, and gravitational waves.
This paper introduces ToMCCA-3, a realistic three-body coalescence model based on the Wigner function formalism and constrained by modern nuclear interaction data, which successfully predicts light (anti)nuclei yields in proton-proton collisions at 13 TeV and demonstrates their sensitivity to nuclear wave functions when compared with ALICE experimental data.
This study utilizes a sample of 120 localized Fast Radio Bursts combined with DESI DR2 Baryon Acoustic Oscillation data and artificial neural networks to constrain the cosmic curvature parameter in a model-independent manner, finding results consistent with a spatially flat Universe while demonstrating the growing potential of FRBs as a precision cosmological probe.