Hep-Th, or high-energy theoretical physics, explores the fundamental building blocks of our universe and the forces that govern them. Researchers in this field use complex mathematics to understand everything from subatomic particles to the behavior of black holes, often pushing the boundaries of what we know about space and time.

At Gist.Science, we monitor the arXiv repository to ensure you stay ahead of the curve in this rapidly evolving discipline. For every new preprint uploaded to arXiv under this category, our team generates both accessible plain-language overviews and detailed technical summaries, making cutting-edge research understandable regardless of your background.

Below are the latest papers in high-energy theoretical physics, curated to help you navigate the most significant recent discoveries.

Plummer Dark Matter Black Hole with Topological Defects: Shadow, Greybody Factors, Quasinormal Modes, and Thermodynamics

This paper presents a static, spherically symmetric black hole solution embedded in a Plummer dark matter halo and a Letelier cloud of strings, systematically analyzing its geometric properties, shadow, deflection angle, scalar perturbations, and thermodynamics to demonstrate that the string-cloud tension parameter α\alpha drives leading-order modifications to all observables while the dark matter halo density ρ0\rho_0 provides only subdominant corrections.

Ahmad Al-Badawi, Faizuddin Ahmed, İzzet Sakallı2026-04-03⚛️ gr-qc

Descending into the Modular Bootstrap

This paper employs machine-learning-style optimization, featuring a novel singular-value-based optimizer and uncertainty estimation, to numerically explore the landscape of two-dimensional conformal field theories with central charges between 1 and 8/7, identifying candidate spectra in a previously uncharted region and suggesting a tighter constraint on the spectral gap near c=1c=1.

Nathan Benjamin, A. Liam Fitzpatrick, Wei Li, Jesse Thaler2026-04-03⚛️ hep-th

Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method

The paper introduces Sven, a computationally efficient natural gradient optimization algorithm that utilizes a truncated singular value decomposition of the loss Jacobian to simultaneously satisfy individual data point residuals, offering faster convergence and lower final loss than standard first-order methods on regression tasks while scaling linearly with the number of retained singular directions rather than quadratically with the number of parameters.

Samuel Bright-Thonney, Thomas R. Harvey, Andre Lukas, Jesse Thaler2026-04-03🤖 cs.LG

Bootstrapping Symmetries in Quantum Many-Body Systems from the Cross Spectral Form Factor

This paper introduces a bootstrap framework that utilizes the cross spectral form factor and spectral correlations to systematically reconstruct the full representation theory and identify hidden finite group symmetries in quantum many-body systems, including their character tables and fusion rules, without prior knowledge of the symmetry group.

Chen Bai, Zihan Zhou, Bastien Lapierre, Shinsei Ryu2026-04-03⚛️ quant-ph

AI usage in string theory, a case study: String Vacua in the Interior of Moduli Space

This paper presents an AI-assisted review of recent computational advances in stabilizing four-dimensional N=1\mathcal{N}=1 Minkowski vacua within the interior of moduli space for specific type IIB string compactifications, highlighting how higher-order flux superpotential terms and exact worldsheet descriptions provide critical data for testing string landscape and swampland conjectures.

Timm Wrase2026-04-03⚛️ hep-th