arXiv research

Bayesian Neural Networks improve precision cosmology from simulations.

A grand challenge of the 21st century cosmology is to accurately estimate the cosmological parameters of our Universe. A major approach to estimating the cosmological parameters is to use the large-scale matter distribution of the Universe. Galaxy surveys provide the means to map out cosmic large-scale structure in thr…

Study shows current simulations are insufficient for optimal neural network training in cosmology.

LSBI approximates likelihood with linear functions for cosmological parameter estimation.

Method trains emulators to estimate posterior probabilities safely.

We study the Laplace spectra of the intrinsic instantaneous metrics on the event and cosmological horizons of a Kerr-Newman de Sitter space-time and prove that the spectral data from these horizons uniquely determine the space-time. This is accomplished by exhibiting formulae relating the parameters of the space-time m…

Bayesian neural networks improve cosmic parameter estimation from modified gravity simulations.

We prove that the leaves of an inverse mean curvature flow provide a foliation of a future end of a cosmological spacetime $N$ under the necessary and sufficent assumptions that $N$ satisfies a future mean curvature barrier condition and a strong volume decay condition. Moreover, the flow parameter $t$ can be used to d…

New method extracts cosmological information from dark matter halo catalogues using graph neural networks.

TRIM improves interpretability of deep neural networks in cosmology.

Adds charged black holes to de Sitter space.

The two-dimensional renormalization group acting as the Ricci flow $Λ\frac{\partial}{\partialΛ} g_{μν} = R_{μν}$ produces a specific 1+3 dimensional space-time metric which describes an expanding universe that starts with a big bang $a \sim t^{\scriptscriptstyle 1/\sqrt3}$ then decelerates until $z=0.2$ then accelerate…

We prove nonlinear stability for a large class of solutions to the Einstein equations with a positive cosmological constant and compact spatial topology in arbitrary dimensions, where the spatial metric is Einstein with either positive or negative Einstein constant. The proof uses the CMC Einstein flow and stability fo…

Deep learning and genetic algorithms speed up cosmological Bayesian inference.

TopoFisher learns topological summaries by maximizing Fisher information, improving parameter efficiency and inference quality.

A new method using normalizing flows speeds up Bayesian model comparison.

Improves inference from sparse data with hybrid summary statistics.

It is well known in astronomy that propagating non-Gaussian prediction uncertainty in photometric redshift estimates is key to reducing bias in downstream cosmological analyses. Similarly, likelihood-free inference approaches, which are beginning to emerge as a tool for cosmological analysis, require a characterization…

Paper introduces a new cosmological volume function and its properties.

Machine learning enhances cosmology through new tools and data analysis.

Study compares MCMC and nested sampling for high-dimensional physics problems.

Study how past eon's matter affects present eon in Penrose's cyclic cosmology.

New mass definition for negative cosmological constant spacetimes.

Study of spacetimes in cosmology without symmetry assumptions.

Estimates high-dimensional posterior densities by marginal distributions and neural networks.

The study examines the index of MOTS in Kerr-Newman-de Sitter spacetime and its relation to mass and charge.

Study shows how 3+1D cosmologies can evolve to de Sitter space under certain conditions.

New CMC existence result for expanding cosmological spacetimes.

Simplifies inference for simulators with or without tractable likelihoods.

New cosmological spacetimes without CMC Cauchy surfaces found.

Prominent approaches to quantum gravity struggle when it comes to incorporating a positive cosmological constant in their models. Using quantization of a complex $\mathrm{SL}(2,\mathbb{C})$ Chern-Simons theory we include a cosmological constant, of either sign, into a model of quantum gravity.

Improved formulation of spinfoam quantum gravity with cosmological constant, ensuring all amplitudes are finite and providing semiclassical asymptotics.

We study Einstein's equation in $(m+n)D$ and $(1+n)D$ warped spaces $(\bar{M},\bar{g})$ and classify all such spaces satisfying Einstein equations $\bar{G}=-\barΛ\bar{g}$. We show that the warping function not only can determine the cosmological constant $\barΛ$ but also it can determine the cosmological constant $Λ$ a…

We discuss a class of (local and non-local) theories of gravity that share same properties: i) they admit the Einstein spacetime with arbitrary cosmological constant as a solution; ii) the on-shell action of such a theory vanishes and iii) any (cosmological or black hole) horizon in the Einstein spacetime with a positi…

Researchers prove a 30-year-old cosmological conjecture about spacetime.

Researchers generalize cosmological models using Finsler geometry.

Next-generation cosmic microwave background (CMB) experiments will have lower noise and therefore increased sensitivity, enabling improved constraints on fundamental physics parameters such as the sum of neutrino masses and the tensor-to-scalar ratio r. Achieving competitive constraints on these parameters requires hig…

Classifies cosmological Finsler spacetimes, finding viable non-stationary models.

In this paper, we analyzed the physical meaning of scalar curvatures for a generalized Riemannian space. It is developed the Madsen's formulae for pressures and energy-densities with respect to the corresponding energy-momentum tensors. After that, the energy-momentum tensors, pressures, energy-densities and state-para…

The paper examines isotropic cosmological space-times with changing sectional curvature.

Simplified proof of cosmic singularity theorem using new mathematical techniques.

The paper introduces a new method to characterize cosmological models using observer-based invariants.

In this paper we propose and discuss a notion of mass for compact static metrics with positive cosmological constant. As a consequence, we characterise the de Sitter solution as the only static vacuum metric with zero mass. Finally, we show how to adapt our analysis to the case of negative cosmological constant, leadin…

New vacuum spacetimes without CMC Cauchy surfaces found.

New mass-type invariants for cosmological space-times.

The study examines conditions that prevent null geodesic lines in spacetimes, impacting cosmological geometry.

Chruściel, Isenberg, and Pollack constructed a class of vacuum cosmological spacetimes that do not admit Cauchy surfaces with constant mean curvature. We prove that, for sufficiently large values of the gluing parameter, these examples are both future and past null geodesically incomplete. The authors are honored to de…

This is the second of two works, in which we discuss the definition of an appropriate notion of mass for static metrics, in the case where the cosmological constant is positive and the model solutions are compact. In the first part, we have established a positive mass statement, characterising the de Sitter solution as…