4035 papers
Quantum gravity represents the frontier where the very large meets the very small, attempting to unify Einstein's theory of gravity with the strange rules of quantum mechanics. This field explores the fundamental fabric of spacetime, seeking to understand how the universe behaves at its most extreme scales, from the heart of black holes to the moment of the Big Bang. Because these concepts often involve complex mathematics, they can feel distant to non-specialists, yet they hold the key to a complete picture of physical reality.
At Gist.Science, we bridge this gap by processing every new preprint in this category directly from arXiv. Our team provides both plain-language explanations and detailed technical summaries for each paper, ensuring that groundbreaking research is accessible to everyone, from curious students to seasoned researchers. Below are the latest papers in quantum gravity, offering fresh insights into the nature of our cosmos.
This paper demonstrates that, when applied to the Starobinsky inflation potential with identical parameters, Lorentzian bump functions are more effective than Gaussian ones at amplifying the curvature power spectrum, thereby generating a greater abundance of primordial black holes and stronger secondary gravitational waves.
This paper demonstrates through numerical simulations that during spherically symmetric dust collapse, a unique, continuous evolution exists beyond shell-crossing singularities where a propagating shock wave forms and the stress-energy tensor transitions into that of a thin shell.
This paper investigates the impact of matter discreteness on gravitational wave propagation using a post-geometrical optics approximation, concluding that while curvature effects from localized particles significantly alter angular diameter distance, the validity of the approximation is limited because large curvature spikes lead to caustic formation that invalidates the method.
This paper provides a comprehensive guide for reconstructing and resampling posterior distributions from LIGO, Virgo, and KAGRA gravitational-wave observations using the Bilby library, offering techniques to modify analysis assumptions and improve efficiency for diverse astrophysical studies.
This paper establishes the covariant phase space formulation of Weyl-transverse gravity on general boundaries, deriving its symplectic structure, Hamiltonian generators, and boundary conditions to clarify how its reduced gauge symmetry and fixed volume form modify the variational principle and first-law thermodynamics compared to General Relativity.
This paper investigates a specific class of vacuum solutions in dimensional static spacetimes with spherical and Euclidean symmetries, identifying two distinct non-trivial classes beyond Minkowski space that exhibit unique mass properties and singularity structures, including Kaluza-Klein bubbles with horizons and naked singularities with negative mass.
This paper presents a fully-relativistic numerical method for initializing and evolving vacuum tensor inhomogeneities during inflation, establishing a correspondence between Cosmological Perturbation Theory and numerical relativity to validate constraint preservation and enable the study of nonlinear gravitational effects on primordial tensor non-Gaussianity.
This paper presents the first full-sky, second-order perturbation theory computation of the angular bispectrum for matter number counts without the Limber approximation, incorporating both Newtonian and relativistic effects, and validates these theoretical predictions against relativistic light-cone simulations while providing publicly available code.
This paper demonstrates through numerical examples that identifying asymptotically flat regions in the maximally extended extreme Reissner–Nordström spacetime does not permit causality violations via timelike or nonradial null geodesics, unlike the non-extreme case, though a formal mathematical proof remains an open challenge.
This paper demonstrates that Vision Transformer (ViT) networks, trained on minimally preprocessed detector strain data, achieve sensitivity comparable to traditional matched-filter methods for continuous gravitational-wave searches while requiring significantly less manual design and hyperparameter tuning than previous convolutional neural network approaches.