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.

⚛️ phenomenology

Observation of quantum effects on radiation reaction in strong fields

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.

Eva E. Los, Elias Gerstmayr, Christopher Arran, Matthew J. V. Streeter, Cary Colgan, Claudia C. Cobo, Brendan Kettle, Th (…)2026-02-16
⚛️ phenomenology

PDFxTMDLib: A High-Performance C++ Library for Collinear and Transverse Momentum Dependent Parton Distribution Functions

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.

R. Kord Valeshabadi, S. Rezaie2026-02-16
⚛️ high-energy experiments

Exploring the BSM parameter space with Neural Network aided Simulation-Based Inference

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.

Atrideb Chatterjee, Arghya Choudhury, Sourav Mitra, Arpita Mondal, Subhadeep Mondal2026-02-16
⚛️ nuclear theory

Linear realization of SU(3) parity doublet model for octet baryons with bad diquark

This paper constructs a linear SU(3)L×SU(3)RSU(3)_L \times SU(3)_R parity doublet model for octet baryons that, by incorporating the (3,6)+(6,3)(3,6) + (6,3) representation containing "bad" diquarks alongside the dominant (3,3ˉ)+(3ˉ,3)(3,\bar{3}) + (\bar{3},3) representation, successfully reproduces the ground-state mass hierarchy (including the Σ\Sigma-Ξ\Xi ordering) and predicts the spectrum of excited states up to 2.5 GeV.

Bikai Gao, Atsushi Hosaka2026-02-16
⚛️ phenomenology

Lazarides-Shafi axion models as Dijkgraaf-Witten theories

This paper formulates Lazarides-Shafi axion models as Dijkgraaf-Witten topological quantum field theories to derive a master formula for the domain wall number and clarify how higher-form symmetries and higher-group structures enable vacuum identification, revealing that even domain-wall-number-one scenarios exhibit nontrivial four-group structures and symmetry-protected topological phases.

Motoo Suzuki, Ryo Yokokura2026-02-16