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 introduces a robust machine learning framework that combines supervised learning with conformal prediction to merge multi-pipeline gravitational wave search results into well-calibrated confidence scores, successfully identifying and validating subthreshold candidates like GW200311_103121 across the GWTC catalogue.
The paper introduces {\sc Akribeia}, a hybrid framework combining physics-informed neural networks with pseudo-spectral refinement to generate and certify precise, continuous rotating black hole solutions in higher-curvature gravity theories, enabling the first construction of such solutions with multiple angular momenta in non-perturbative regimes.
This paper investigates the deflection of light around a rotating Kerr-Bertotti-Robinson black hole using a material medium approach, revealing that the presence of a uniform magnetic field enhances gravitational lensing and alters the spacetime geometry, while thermodynamic analysis shows entropy decreases with both magnetic field strength and rotation, whereas Hawking temperature increases with the magnetic field but decreases with the spin parameter.
This paper introduces a hierarchical Bayesian inference framework that leverages non-Gaussian information from both individual bright sources and power spectrum fluctuations in pulsar timing array data to distinguish between astrophysical and primordial origins of the nanohertz gravitational wave background while simultaneously inferring the population properties of supermassive black hole binaries.
This paper demonstrates that interactions between the adiabatic curvature perturbation and a massive entropic scalar environment during a transient Ultra-Slow-Roll inflationary phase induce distinct non-Markovian decoherence effects that significantly alter the primordial scalar power spectrum and generate unique signatures in the stochastic background of Scalar-Induced Gravitational Waves, potentially offering observable evidence for open quantum dynamics in the early universe.
This paper employs cosmic age-based parameterizations (PAge and MAPAge) within an improved inverse distance ladder framework using diverse late-universe datasets to model-independently measure a Hubble constant of km s Mpc, thereby reducing the tension to the level and confirming a flat universe consistent with current observational data.
This paper demonstrates that for inferring the Hubble constant via the mass spectrum method using current and near-future gravitational-wave data, employing simpler models that omit spin precession and higher-order multipoles yields comparable results to more complex models while reducing computational costs by a factor of six.
This paper presents a hybrid search pipeline combining matched filtering and deep learning to analyze Advanced LIGO's third observing run, demonstrating comparable sensitivity to existing methods for high-mass binary black hole mergers while identifying a new, promising candidate with a high probability of containing an intermediate-mass black hole.
This paper demonstrates that black hole ringdown waveforms remain robust against stochastic horizon-scale structures due to a phase averaging mechanism, establishing that any detectable deviations would require macroscopic spatial coherence and thus ruling out the observability of incoherent quantum foam in static Schwarzschild models.
By combining Type Ia supernova peculiar velocity measurements with CMB data, this study demonstrates that these datasets are highly complementary for simultaneously constraining matter clustering (), curvature (), and the growth index (), revealing hints of positive curvature and showing that including SH0ES data recasts the Hubble tension as a preference for negative curvature and suppressed structure growth.