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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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48 results for cosmological time function

Paper introduces a new cosmological volume function and its properties.

problem Introducing a new cosmological volume function.
method Introduces and analyzes the cosmological volume function τ_V, showing it's continuously differentiable.
result τ_V leads to a canonical splitting of the metric tensor and a canonical Wick-rotated Riemannian metric.

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

problem Cosmological space-times with changing sectional curvature.
method Analysis of a family of geometrically well-behaved cosmological space-times foliated by isotropic hypersurfaces.
result Only space-time isometries ensure the rigidity properties of isotropic cosmological space-times.

Let (M,g)(M,g) be a time oriented Lorentzian manifold and dd the Lorentzian distance on MM. The function τ(q):=supp<qd(p,q)τ(q):=\sup_{p< q} d(p,q) is the cosmological time function of MM, where as usual p<qp< q means that pp is in the causal past of qq. This function is called regular iff τ(q)<τ(q) < \infty for all qq and also $τ\to 0…

1997-09-30abs ↗pdf ↗

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

2016-10-14abs ↗pdf ↗

This paper gives a new proof that maximal, globally hyperbolic, flat spacetimes of dimension n3n\geq 3 with compact Cauchy hypersurfaces are globally foliated by Cauchy hypersurfaces of constant mean curvature, and that such spacetimes admit a globally defined constant mean curvature time function precisely when they a…

2006-04-22abs ↗pdf ↗

Proves limit curve theorem for incomplete metric spaces, applies to null distance in Lorentzian manifolds.

problem Control of Lorentzian lengths of limit curves in incomplete metric spaces.
method Proves limit curve theorem for incomplete metric spaces and applies to null distance.
result Strong control on Lorentzian lengths of limit curves in Sormani and Vegas' null distance.

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

2004-03-04abs ↗pdf ↗

We consider spacetimes consisting of a manifold with Lorentzian metric and a weight function or scalar field. These spacetimes admit a Bakry-Émery-Ricci tensor which is a natural generalization of the Ricci tensor. We impose an energy condition on the Bakry-Émery-Ricci tensor and obtain singularity theorems of a cosmol…

2013-12-12abs ↗pdf ↗

Null distance encodes causal structure in spacetimes.

problem Encoding causal structure in Lorentzian manifolds.
method Using null distance defined by Sormani and Vega, and proving causal structure is encoded by null distance.
result Lorentzian isometry between spacetimes with bijective map preserving null distance and cosmological time function.

This paper is motivated by the non-linear stability problem for the expanding region of Kerr de Sitter cosmologies in the context of Einstein's equations with positive cosmological constant. We show that under dynamically realistic assumptions the conformal Weyl curvature of the spacetime decays towards future null inf…

2016-10-13abs ↗pdf ↗

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…

2017-11-06abs ↗pdf ↗

In this paper we study the flat (n+1)-spacetimes admitting a Cauchy surface diffeomorphic to a compact hyperbolic n-manifold. We show how to construct a canonical future complete one among all such spacetimes sharing the same holonomy. We study the geometry of such a spacetime in terms of its canonical cosmological tim…

2003-11-03abs ↗pdf ↗

The paper studies convergence of cosmological spacetimes using null distance.

problem Convergence of cosmological spacetimes with compact slices.
method Using null distance and Gromov-Hausdorff convergence, the paper establishes convergence results for spacetimes with mild extension properties.
result Uniform convergence of null distances and Gromov-Hausdorff convergence for monotone sequences of spacetimes.

New null distance bounds confirm Big Bang singularity in cosmological models.

problem Understanding the geometry of spacetime near Big Bang singularities.
method Developed a new null distance metric for temporal functions and applied it to cosmological models.
result Null distance is bounded by a constant multiple of Riemannian distance on level sets with constant gradient norm.

A proof is given that the maximal Fermi coordinate chart for any comoving observer in a broad class of Robertson-Walker spacetimes consists of all events within the cosmological event horizon, if there is one, or is otherwise global. Exact formulas for the metric coefficients in Fermi coordinates are derived. Sharp uni…

2012-10-29abs ↗pdf ↗

Deep learning and genetic algorithms speed up cosmological Bayesian inference.

problem Substantial computational demands in Bayesian inference for cosmological parameter estimation.
method Deep learning using feedforward neural networks to approximate likelihood functions dynamically, optimized with genetic algorithms.
result Significant speed-up in Bayesian inference process for cosmological models and datasets.

We show that any metric on S2S^2 with Gauss curvature KκK \geq -κ admits a C1,1C^{1,1}-isometric embedding into the hyperbolic space with sectional curvature κ. We also give a sufficient condition for a metric on S2S^2 to be isometrically embedded into anti-de Sitter spacetime with the prescribed cosmological time fun…

2014-01-23abs ↗pdf ↗

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

problem Equivalence problem for cosmological models in four-dimensional gravity theories.
method Modified Cartan-Karlhede algorithm adapted to fundamental observers, including derivatives of the time-like vector field.
result A list of invariants that completely characterize cosmological models, independent of coordinates.

Study of Bondi-Sachs formalism for massless scalar field with zero cosmological constant.

problem Analyzing the Bondi-Sachs formalism for Einstein's massless scalar field equations.
method Asymptotic expansions and peeling property for Bondi-Sachs metrics and scalar fields.
result Positivity of Bondi energy-momentum under specific conditions.

Physics-informed neural networks improve baryonic predictions from dark matter simulations.

problem Recreating hydrodynamic simulations from dark matter requires expensive and time-consuming computations.
method Combining neural network architectures with physical constraints and using Kullback-Leibler divergence for prediction comparison.
result Improved accuracy of baryonic predictions based on dark matter halo properties, successful recovery of the metallicity relation, and preserved scatter.

The universe's shape and size are determined in general cosmological models.

problem Determining the shape and size of the universe in general cosmological models.
method Using differential geometry and extensions of the Bonnet-Myers theorem, the researchers derived conditions for a finite universe and provided a list of possible topologies.
result The spatial sections of the universe can be either S1imesS2S^1 imes S^2, S1ildeimesS2S^1 ilde{ imes}S^2, S1imesRP2S^1 imes\mathbb{RP}^2, RP3#RP3\mathbb{RP}^3 \# \mathbb{RP}^3, or covered by the sphere S3S^3 or torus T3T^3.

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

problem Insufficient training data for neural networks in cosmological inference.
method Empirical neural scaling law and Cramer-Rao bound to forecast training simulations needed.
result Current simulation suites do not provide sufficient training data for optimal neural network performance.

Study shows inflation in 3+1D cosmologies with bounded scalar potential and specific symmetry.

problem Understanding inflation in 3+1D cosmologies with specific constraints.
method Mean curvature flow and asymptotic analysis of metric variations, stress-energy tensor, and inflaton field dynamics.
result Inflation occurs in 3+1D cosmologies with specific constraints, demonstrating it is possible with inhomogeneous initial conditions.

Bayesian Neural Networks improve precision cosmology from simulations.

problem Extracting precise cosmological parameters from complex simulations.
method Using Bayesian Neural Networks on The Quijote simulations.
result Demonstrates BNNs' ability to estimate associated uncertainties and complex output distributions.

Genetic algorithms optimize neural networks for cosmological data analysis.

problem Inaccurate results from neural networks due to poor hyperparameter selection.
method Used genetic algorithms to optimize hyperparameters of neural networks.
result Genetic algorithms improve neural network performance in cosmological data analysis.

Theorem proves topological censorship for universes with positive cosmological constant.

problem Proving topological censorship for spacetimes with positive cosmological constant.
method Developed a new theorem assuming eventual isolation of black hole collections.
result Regions near black hole collections have trivial fundamental group.

The two-dimensional renormalization group acting as the Ricci flow ΛΛgμν=RμνΛ\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 at1/3a \sim t^{\scriptscriptstyle 1/\sqrt3} then decelerates until z=0.2z=0.2 then accelerate…

2019-09-03abs ↗pdf ↗

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

problem Quantifying cosmological information from large-scale structure data.
method Implicit likelihood approach with Information Maximising Neural Networks (IMNNs) on graph representations of dark matter halo catalogues.
result Graph neural network summaries can extract information from noisy catalogues and improve parameter constraints.

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

problem Efficiently sampling high-dimensional Bayesian posterior distributions in particle physics and cosmology.
method Review and comparison of MCMC and nested sampling techniques on high-dimensional test functions and real physics examples.
result Modern MCMC algorithms can outperform nested sampling in certain cases, highlighting implementation details.

For a stable marginally outer trapped surface (MOTS) in an axially symmetric spacetime with cosmological constant Λ>0Λ> 0 and with matter satisfying the dominant energy condition, we prove that the area AA and the angular momentum JJ satisfy the inequality 8πJA(1ΛA/4π)(1ΛA/12π)8π|J| \le A\sqrt{(1-ΛA/4π)(1-ΛA/12π)} which is saturated pre…

2015-01-28abs ↗pdf ↗