4400 papers
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.
This paper revisits the Salecker–Wigner–Peres stationary quantum clock to identify and remove a universal low-energy threshold singularity, thereby isolating the true resonant delay contribution and providing a refined observable that distinguishes kinematic threshold effects from pole-sensitive scattering dynamics.
This paper demonstrates that in a thermal bath of gravitons, metric fluctuations induce a probabilistic uncertainty in the causal structure of a massless scalar field, causing the lightcone to spread with a variance that grows cubically in time and linearly with temperature.
This paper extends Nielsen's geometric approach to quantum complexity by introducing a hierarchy of cost factors associated with varying degrees of non-locality, deriving the resulting modified geodesic equations, and demonstrating how this generalized framework reshapes the structure and scaling of conjugate points in both single-qubit and many-body SYK-type systems.
This paper refines a previously constructed two-field DHOST bouncing model to ensure its predictions for non-Gaussianity align with observations and demonstrates that the model remains stable, free of superluminality, and weakly coupled at the non-linear level, thereby establishing it as a fully viable cosmological scenario.
This paper investigates a specific class of half-BPS boundary conditions for 4d circular quiver gauge theories engineered by D4-branes, characterizing their unique winding solutions and proposing a maximal-winding configuration as the S-dual of the pure Neumann boundary condition.
This paper proposes that introducing an additional scalar field with a matter-like equation of state can dilute gravitino dark matter abundance, thereby resolving the tension between high reheating temperatures needed for thermal leptogenesis and future collider constraints on gluino masses.
This paper demonstrates that imposing off-shell supersymmetry closure on a CPT-even effective action in the Lorentzian IIB matrix model algebraically forces the decoupling of internal non-Abelian flux and selects a -Minkowski-like macroscopic sector, thereby providing a kinematic mechanism for relative effective compactification without relying on classical solutions.
This study demonstrates that event-shape engineering in Pb-Pb collisions provides a sharper discrimination between sequential and simultaneous charm hadronization scenarios by revealing a geometry-dependent elliptic-flow splitting () and a species-specific response slope hierarchy that are unique to the sequential model.
This paper investigates the asymptotic behavior of complex - symbols, demonstrating that when their parameters scale according to the dihedral angles of a hyperideal hyperbolic tetrahedron, the symbols relate to the tetrahedron's volume and Gram matrix determinant, with potential implications for the complex Liouville string in specific cases.
This paper employs conformal perturbation theory to analyze the renormalization group flows of protected displacement and tilt operators in surface defects within and other multiscalar models, successfully reproducing known results, constructing new examples, and identifying novel features like vortices, while explicitly acknowledging the significant role of generative AI in the research process.