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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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3226449661,288 · Jun 202019922001200920172026
48 results for smooth initial data

Smooth dec initial data sets may not extend to smooth spacetimes.

problem Whether every dec initial data set can be extended to a smooth spacetime.
method Examined the converse of the dominant energy condition for initial data sets and spacelike hypersurfaces.
result Not all dec initial data sets can be extended to smooth spacetimes.

Proves rigidity for specific initial data sets under the dominant energy condition.

problem Rigidity of initial data sets with boundary and convex polytopes.
method Solution of boundary value problems for Dirac operators and approximations by manifolds with smooth boundary.
result Proves rigidity for compact smooth spin manifolds and convex polytopes under the dominant energy condition.

Minimal existence time for Willmore flow established for smooth and weak Lipschitz initial data.

problem Existence time of the Willmore flow for various initial conditions.
method Established minimal existence time for Willmore flow using geometric data and conservation laws.
result Minimal existence time is a function of geometric data for general weak Lipschitz initial data.

Constructs initial data leading to apparent horizons and tests Penrose Inequality.

problem Testing Penrose Inequality in dynamical spacetimes.
method Scale critical initial data for Einstein vacuum system, constructing Cauchy data.
result Penrose Inequality holds in an open region of the future of initial data.

Constructs initial data for multiple black holes with specified ADM parameters.

problem Forming multiple black holes with specific ADM parameters.
method Smooth, asymptotically flat vacuum initial data with prescribed ADM energy, momentum, and angular momentum.
result Maximal development of data results in spacetimes containing multiple black holes.

The paper proves smoothness of mean curvature flow for generic initial data in 3D and 4D.

problem Smoothness of mean curvature flow for generic initial data.
method Long-time existence and uniqueness result for ancient mean curvature flows.
result Smooth mean curvature flow until disappearance in a round point for low-entropy hypersurfaces in 4D.

We consider compact convex hypersurfaces contracting by functions of their curvature. Under the mean curvature flow, uniformly convex smooth initial hypersurfaces evolve to remain smooth and uniformly convex, and contract to points after finite time. The same holds if the initial data is only weakly convex or non-smoot…

2011-04-05abs ↗pdf ↗

For asymptotically flat initial data of Einstein's equations satisfying an energy condition, we show that the Penrose inequality holds between the ADM mass and the area of an outermost apparent horizon, if the data are restricted suitably. We prove this by generalizing Geroch's proof of monotonicity of the Hawking mass…

2002-01-08abs ↗pdf ↗

Smooth solutions found for modified mean curvature flow in Riemannian manifolds.

problem Existence of smooth solutions for modified mean curvature flow.
method A priori estimates for modified mean curvature flow in Riemannian manifolds with Killing vector field.
result Existence of smooth, entire, longtime solutions for modified mean curvature flow with smooth initial data.

PNN-smoothing improves kk-means clustering by merging subsets' clusterings.

problem Improving kk-means clustering initialization efficiency and effectiveness.
method Split dataset into subsets, cluster each subset, merge with PNN method.
result PNN-smoothing enhances kk-means++ seeding, reducing costs.

A classical problem in general relativity is the Cauchy problem for the linearised Einstein equation (the initial value problem for gravitational waves) on a globally hyperbolic vacuum spacetime. A well-known result is that it is uniquely solvable up to gauge solutions, given initial data on a spacelike Cauchy hypersur…

2018-02-16abs ↗pdf ↗

This work removes logarithmic singularities from hyperboloidal initial data without creating new ones.

problem Logarithmic singularities in hyperboloidal initial data sets.
method Evolutionary framework of the constraint equations and generalization of Beyer and Ritchie's result.
result Generic solutions of the constraint equations are free of logarithmic singularities.

In this paper, we introduce a new parabolic equation on Kähler manifolds. The static point of this flow is related to the existence of a lower bound of the Mabuchi energy. In this paper, we prove the flow always exists for all times for any initial smooth data. Further more, if the initial metric has non-negative bisec…

2000-09-29abs ↗pdf ↗

In this paper, we prove that there exists a dimensional constant δ>0δ> 0 such that given any background Kähler metric ωω, the Calabi flow with initial data u0u_0 satisfying \begin{equation*} \partial \bar \partial u_0 \in L^\infty (M) \text{ and } (1- δ)ω< ω_{u_0} < (1+δ)ω, \end{equation*} admits a unique short time so…

2017-01-24abs ↗pdf ↗

We construct a sequence of smooth Ricci flows on T2T^2, with standard uniform C/tC/t curvature decay, and with initial metrics converging to the standard flat unit-area square torus g0g_0 in the Gromov-Hausdorff sense, with the property that the flows themselves converge not to the static Ricci flow g(t)g0g(t)\equiv g_0, bu…

2019-04-25abs ↗pdf ↗

In this paper we investigate the singularities of Lagrangian mean curvature flows in Cm\mathbf{C}^m by means of smooth singularity models. Type I singularities can only occur at certain times determined by invariants in the cohomology of the initial data. In the type II case, these smooth singularity models are asympto…

2015-05-07abs ↗pdf ↗

FCNv2 robustness tested under noise and random initial conditions.

problem Assessing AI weather forecasting model robustness to input noise.
method Two experiments with varying noise levels and random initial conditions.
result FCNv2 preserves hurricane features under low to moderate noise, but underestimates intensity and persistence.

We develop the idea of using an algebraic-geometry approach to classical differential geometry problems. Consider an orthogonal net constructed according to algebraic-geometric data we obtain a set of smooth orthogonal nets that are Ribaucour transformations of the initial orthogonal net.

2019-12-29abs ↗pdf ↗

In this paper, we study the torsion flow which is served as the CR analogue of the Ricci flow in a closed pseudohermitian manifold. We show that there exists a unique smooth solution to the CR torsion flow in a small time interval with the CR pluriharmonic function as an initial data. In spirit, it is the CR analogue o…

2018-04-18abs ↗pdf ↗

Study solves a generalized Christoffel-Minkowski problem using curvature flow.

problem Generalization of the LpL_{p}-Christoffel-Minkowski problem.
method Anisotropic curvature flow to derive long-time existence and smooth solutions.
result Existence of smooth solutions for c=1c=1 under certain initial data.

Convex hypersurfaces in hyperbolic space evolve to geodesic spheres.

problem Volume preserving Gauss curvature flow of convex hypersurfaces in hyperbolic space.
method Volume preserving flow with speed given by Gauss curvature power α, using Alexandrov reflection and hyperbolic curvature measures.
result Smooth solution remains convex and converges to a geodesic sphere exponentially.

S-GAI initializes MLPs using spectral geometry from data, improving performance.

problem Lack of guidance on initial weights encoding data geometry.
method S-GAI uses SVD to estimate spectral class geometry, initializing MLPs from training data.
result S-GAI-initialized MLPs start from a more informative hidden state and achieve comparable accuracy.

Hierarchical randomized smoothing improves model robustness for complex data.

problem Certifying robustness on complex data (e.g. images, graphs) is challenging.
method Add random noise to a randomly selected subset of entities in a hierarchical manner.
result Hierarchical randomized smoothing yields stronger robustness guarantees with high accuracy.

The paper proves a spacetime positive mass theorem for singular initial data sets.

problem Proving the positive mass theorem for initial data sets with corners.
method Extending Hirsch-Kazaras-Khuri's method to singular cases using Hirsch-Miao-Tsang ideas.
result Integral lower bound on spacetime mass and characterisation of zero mass.

Gradient descent with logistic loss can interpolate deep networks with smoothed ReLU activations under certain conditions.

problem Conditions for gradient descent to drive logistic loss to zero in deep networks with smoothed ReLU activations.
method Gradient descent applied to fixed-width deep networks with smoothed ReLU approximations (e.g., Swish, Huberized ReLU).
result Gradient descent can drive logistic loss to zero under specific conditions, providing bounds on convergence rate.

Randomly initialized ReLU networks of depth two can approximate smooth functions well.

problem Approximation power of two-layer networks of random ReLUs.
method Harmonic analysis and ridgelet representation theory for upper bounds, dimensionality arguments for lower bounds.
result Near-matching upper and lower bounds for L2L_2-approximation and Sobolev norms.