3826 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 in non-maximally quantum chaotic systems, pole-skipping points of few-body operators form trajectories encoding the Lyapunov exponent, which can be interpreted as Regge trajectories of stringy excitations probing the horizon structure of a dual stringy black hole.
This paper explores how next-generation detectors can utilize high-frequency kilohertz gravitational-wave signals from core-collapse supernovae—arising from proto-neutron star oscillations, black hole formation, QCD phase transitions, and alternative gravity theories—to probe extreme matter and identify physics beyond the Standard Model.
This paper constrains the Emergent Fractional Fractal cosmological model using joint likelihood analyses of various cosmological datasets, finding that while the fractal dimension is tightly constrained near the standard value of 2, the model offers no significant improvement over the standard CDM model according to Bayesian Information Criterion comparisons.
This paper proposes a Dark Matter-Baryon Separability condition to demonstrate how dark matter deficient galaxies serve as unique probes for constraining late-time dark matter interactions, dissipation, and halo stability, thereby complementing cosmological and laboratory studies.
This paper demonstrates that a rigid spherical shell enclosing a degenerate Schwarzschild-Klinkhamer wormhole possesses zero proper mass while maintaining the same exterior Schwarzschild geometry and ADM mass as a standard shell, implying that the gravitational field is entirely carried by the wormhole geometry.
This paper establishes a formal framework for electromagnetic wave propagation in metric-affine geometries by constructing gauge-invariant models that reveal how torsion and non-metricity can alter light cones, induce birefringence, and modify intensity transport, thereby providing a basis for testing these geometric effects through astrophysical observations like black-hole imaging.
This paper investigates nucleon spectra by refining the Einstein-dilaton holographic model with new parameters and extending the approach to a Starobinsky-dilaton gravity framework, ultimately comparing both improved models against soft-wall predictions and experimental data.
This paper presents numerical solutions to the coupled Einstein-Dirac-Maxwell system for static, spherically symmetric two-fermion configurations, revealing that while charged Dirac stars exist, they are always gravitationally unbound.
This paper presents a linearly stable kinetically braided dark energy model with momentum exchange that successfully achieves an upward phantom-divide crossing while simultaneously suppressing cold dark matter structure growth through a reduced effective gravitational coupling, yielding distinct signatures in the matter power spectrum and CMB temperature anisotropies.
This paper proposes a Bayesian nonparametric framework utilizing matrix-gamma process priors and adaptive MCMC sampling to directly estimate the Hermitian positive-definite spectral density matrix of correlated noise in next-generation gravitational-wave detector networks, thereby improving parameter estimation accuracy for signals from missions like LISA and the Einstein Telescope.