3949 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 derives a universal formula for the anomalous scaling of multipole moments in classical general relativity using effective field theory methods, demonstrating that this scaling is determined by gravitational wave phase shifts and proposing a novel resummation of universal short-distance logarithms to improve gravitational waveform modeling for compact binary systems.
This paper derives a closed formula for 5D Schwarzschild-Tangherlini black hole scalar wave scattering using the Nekrasov-Shatashvili function and computes non-vanishing, renormalization group running tidal Love numbers up to by matching effective field theory with ultraviolet solutions.
This paper establishes a connection between the Mano-Suzuki-Takasugi formalism and worldline effective field theory to analyze the dynamical tidal response of non-rotating black holes in general relativity, revealing that renormalized tidal response functions and resulting Love numbers are inherently scheme-dependent and sensitive to initial renormalization conditions.
This paper demonstrates that a Thurston-based theory of gravity admits shear-free and static solutions across all Bianchi-Kantowski-Sachs topologies and ensures isotropization with a positive cosmological constant while preventing recollapse under the weak energy condition, thereby resolving specific limitations of General Relativity without introducing additional parameters.
This paper proposes that cosmic acceleration arises naturally from the nonlinear dynamics of a universe containing equal amounts of positive and negative Bondi masses, where the transition from a weakly to a strongly coupled gravitational regime drives a shift from ballistic expansion to uniform acceleration without requiring dark energy.
FluxMC is a machine learning-enhanced framework that combines Flow Matching with Parallel Tempering MCMC to overcome the computational bottlenecks of traditional Bayesian inference, enabling rapid and high-fidelity parameter estimation for space-based gravitational-wave observations without compromising between model accuracy and analysis speed.
This paper proposes a novel concept of astrophysical mirroring within the Schwarzschild framework, demonstrating through theoretical and numerical analysis that the extreme spacetime curvature around compact massive objects can bend light rays to create mirror-like reflection images of distant sources.
This paper computes the stochastic gravitational wave background generated by parametric resonance of a spectator scalar field during reheating, deriving a master formula that predicts a detectable high-frequency signal () while validating the analytical framework against nonlinear lattice simulations to capture both superhorizon evolution and fragmentation effects.
This paper establishes a historical optical foundation for stationary vacuum Kerr--Schild spacetimes by demonstrating how a single complex optical seed, derived from expansion and twist, algebraically reconstructs the spacetime congruence and serves as the normalized zeroth-copy data that generates both the metric profile and the associated single-copy gauge field within the double-copy framework.
This paper introduces a causal convolutional neural network trained on RNS-generated data to rapidly and accurately reconstruct observables for fast-rotating neutron stars, reducing computation time from approximately 30 minutes to 50 milliseconds per configuration and enabling efficient inference analyses that were previously hindered by the high cost of traditional two-dimensional modeling.