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.

⚛️ quantum physics

Physics-Informed Classical and Quantum Neural Networks for One-Dimensional Schrodinger Eigenvalue Problems

This paper demonstrates that Physics-Informed Classical and Quantum Neural Networks can accurately solve one-dimensional time-independent Schrödinger eigenvalue problems for harmonic and square well potentials without supervised data, with the quantum approach showing superior convergence reliability for higher excited states compared to classical methods and traditional numerical solvers.

Tariq Mahmood, Waqas Arshad, Bilal Naseer, Alfredo Raya2026-09-22
⚛️ phenomenology

Gravitational Waves from Long Strings and Loops

This paper computes the gravitational wave spectrum from a global cosmic string network in the scaling regime by analytically deriving the infrared contribution from both long strings and loops using a generalized unconnected segment model, and employing a data-driven method to model the ultraviolet regime, ultimately mapping current and future constraints on the axion symmetry-breaking scale and mass.

Christos Litos, Sarunas Verner, Wei Xue, Fengwei Yang2026-09-22
⚛️ phenomenology

Machine Learning for Invisible Dark Boson Searches at the Electron-Ion Collider

This study investigates the potential of boosted decision trees to improve invisible dark boson selection at the Electron-Ion Collider compared to optimized rectangular cuts, finding that while machine learning offers no consistent advantage using only electron information, it provides a slight improvement when nuclear four-momentum transfer (tt) is included.

Rojae Mighty, Ankush Reddy Kanuganti2026-09-22
🔭 astrophysics

Axio-Dilaton Dark Energy: A Dynamical Systems and Bayesian Inference Analysis

This paper employs dynamical systems analysis and Bayesian inference on Type Ia Supernovae, BAO, and Planck 2018 data to show that a supergravity-motivated axio-dilaton dark energy model with a curved field-space metric can explain cosmic acceleration but is only marginally preferred over the standard Λ\LambdaCDM model.

Mario Ramos-Hamud, Gabriela García-Arroyo, Fernando Quevedo, J. Alberto Vázquez2026-09-22
⚛️ phenomenology

Probing light axion-like particles in vector boson fusion at CMS with data parking and scouting

This paper proposes a novel strategy using CMS data parking and scouting techniques combined with tracker-based reconstruction of merged photon pairs to overcome trigger thresholds and resolve boosted decays, thereby enabling the first sensitivity to light axion-like particles in the 10 MeV–10 GeV mass range through vector boson fusion.

Sena Durgut, Mariel Peczak, Gonzalo Alonso-Álvarez, Chiara Amendola, Matteo Cremonesi, Joerg Jaeckel, Matteo Marchegiani2026-09-22
⚛️ phenomenology

New bounds on light scalars from the tip of the red giant branch

By implementing finite-temperature field theory calculations of resonant plasmon conversion into the MESA stellar evolution code to self-consistently model red giant cores, this study establishes the tightest constraints to date on light scalar-electron couplings and Higgs portal mixing angles by comparing simulated tip of the red giant branch magnitudes with observations of 27 Milky Way globular clusters.

Natnael Debru, Audrey Fung, Saniya Heeba, Hugo Schérer, Katelin Schutz, Aaron C. Vincent2026-09-22
⚛️ general relativity

Black Holes as Frequency-Dependent Filters of Stochastic Gravitational Waves

This paper quantifies how black holes act as frequency-dependent filters for stochastic gravitational waves, demonstrating that while horizon absorption and superradiance can theoretically distort or amplify signals, these effects are negligible for cosmological populations and are most likely observable only in rare, nearby, or specifically aligned systems.

Sefi Katznelson, Aidan Minger, Stefano Profumo2026-09-22