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48 results for lightcone cuts

Study of quasilocal energy in higher dimensions, focusing on small sphere limits.

problem Understanding quasilocal energy in higher dimensions and its small sphere limits.
method Generalized quasilocal energy definitions, evaluated along lightcone cuts, and compared with known energies.
result The small sphere limits of quasilocal energy in higher dimensions are not proportional to the Bel-Robinson superenergy, challenging its role as gravitational energy.

Study on Bertrand lightcone framed curves in Lorentz-Minkowski 3-space.

problem Analyzing mixed types of curves with singular points in Lorentz-Minkowski 3-space.
method Using lightcone frame to consider Bertrand types for lightcone framed curves.
result Existence conditions of Bertrand lightcone framed curves in all cases.

Study on focal surfaces of lightcone framed surfaces in Lorentz-Minkowski 3-space.

problem Investigate differential geometry properties of focal surfaces of lightcone framed surfaces.
method Introduced lightcone frame to define lightcone framed surfaces, then investigated their differential geometry properties.
result Investigated differential geometry properties of focal surfaces of lightcone framed surfaces.

Study of lightcone framed surfaces in Lorentz-Minkowski 3-space, focusing on curvature behavior.

problem Investigate differential geometric properties of lightcone framed surfaces.
method Introduced modified frame to study the properties of lightcone framed surfaces.
result Showed behavior of Gaussian and mean curvatures at lightlike and singular points.

Past lightcones of certain points in globally hyperbolic spacetimes determine the entire spacetime.

problem Determining the entire spacetime from the past lightcone of a point.
method Analyzing properties of globally hyperbolic spacetimes and using null lines and observer horizons.
result Past lightcones of certain points in globally hyperbolic spacetimes determine the entire spacetime (up to isometry).

Study of null mean curvature flow on de Sitter lightcone, related to 2d-Ricci flow.

problem Analyzing singularity formation and asymptotic behavior of null mean curvature flow.
method Rescaling procedure to relate to 2d-Ricci flow, singularity analysis, asymptotic behavior study.
result Ancient solutions to the flow can be understood in terms of 2d-Ricci flow.

Constructs foliations of lightcones using surfaces of constant spacetime mean curvature.

problem Creating foliations of lightcones with specific geometric properties.
method Employing a geometric flow inspired by Huisken-Yau's approach for Riemannian settings.
result Initial data converges exponentially to an STCMC surface under area preserving null mean curvature flow.

Paper proves uniqueness of specific spacetime surfaces in a lightcone.

problem Proving uniqueness of surfaces of constant spacetime mean curvature in a lightcone.
method Used a fairly generic notion of asymptotic flatness to prove uniqueness.
result Unique foliation by surfaces of constant spacetime mean curvature exists under weaker assumptions.

New perspective on Ricci flow on spheres using Minkowski spacetime.

problem Classifying singularity models for null mean curvature flow in Minkowski spacetime.
method Equivalence of 2d-Ricci flow and null mean curvature flow on lightcones.
result Classification of singularity models for null mean curvature flow.

Study shows constant curvature convex hypersurfaces on hyperboloids are parts of hyperboloids.

problem Characterizing convex hypersurfaces with constant curvature on hyperboloids.
method Analyzing hypersurfaces with constant higher order mean curvature and constant boundary angle.
result Hypersurfaces with constant curvature on hyperboloids are parts of hyperboloids.

Study on stability of surfaces in null cones under area-preserving variations.

problem Investigating stability of spacelike cross sections of null cones.
method Area-preserving variations, Hawking energy analysis, spherical cross sections.
result Only round spheres are stable cross sections of the standard Minkowski lightcone.

We prove effective uniformization for nearly round 2-spheres and investigate their stability.

problem Proving effective uniformization for nearly round 2-spheres and their stability.
method Utilizing an identity related to the third-order differential of the conformal factor, and an isometric embedding of a round sphere into Euclidean space using an orthogonal basis of the first eigenspace of the Laplacian operator.
result We provide a simplified proof of effective uniformization and its stability.

Generalizes Fermat's principle for wave propagation in cone structures.

problem Wave propagation in complex media with discontinuities and anisotropy.
method Generalizes Fermat's principle to smooth interfaces separating two cone structures representing wave propagation in various media.
result Conditions for critical points of arrival time functional, generalizing Snell's law and reflection.

In a joint work with Saji, the second and the third authors gave an intrinsic formulation of wave fronts and proved a realization theorem of wave fronts in space forms. As an application, we show that the following four objects are essentially same; * conformally flat n-manifolds (n>=3) with admissible singular points …

2010-01-25abs ↗pdf ↗

NeuralCut learns to select cutting planes by looking ahead, outperforming traditional methods.

problem Selecting effective cutting planes for MILP optimization.
method Imitation learning on a lookahead expert to train a neural network for cut selection.
result NeuralCut outperforms standard baselines in cut selection for MILP benchmarks.

Differentiable cutting-plane layers solve parametric mixed-integer linear optimization problems.

problem Solving parametric mixed-integer linear optimization problems with changing data.
method Introducing cutting-plane layers (CPLs) for differentiable cutting-plane generation.
result The algorithm computes solutions with low integrality gaps and generalizes to unseen instances.

NeVI-Cut uses neural networks to efficiently propagate uncertainty without feedback.

problem Efficiently propagating uncertainty in downstream Bayesian analysis without feedback.
method NeVI-Cut combines neural networks and normalizing flows for variational inference.
result NeVI-Cut achieves significant computational gains and higher accuracy than traditional methods.

Paper connects probability density cuts to graph theory eigenfunctions.

problem Developing sparse cuts for probability densities.
method Defines sparse cuts and principal eigenfunctions for probability densities, proving Cheeger and Buser inequalities.
result No such inequalities hold for prior definitions, proving new inequalities for probability densities.

Stability of cut locus under metric perturbations in compact Riemannian manifolds.

problem Stability of cut locus under C2C^2-perturbations of the metric.
method Proving stability with respect to the Hausdorff metric of the cut locus under C2C^2 perturbation of the metric.
result The Hausdorff distance between cut loci converges to zero as the metrics converge.

Study shows convergence rates for Cheeger cuts on data clouds.

problem Optimizing graph cuts for clustering data sampled from a manifold.
method Analyzes statistical properties of Cheeger cuts on proximity graphs built from data.
result Obtains high probability convergence rates for Cheeger constant and cuts.

Unified framework for differentiable graph partitioning with probabilistic cuts.

problem Lack of general guarantees and principled gradients in prior probabilistic relaxations of graph cuts.
method Unified probabilistic framework covering a wide class of cuts, including Normalized Cut, with tight analytic upper bounds.
result Rigorous, numerically stable foundation for scalable, differentiable graph partitioning.

The paper studies helicoidal surfaces of non-lightlike frontals in Lorentz-Minkowski 3-space.

problem Investigating the properties and singularities of helicoidal surfaces in Lorentz-Minkowski space.
method Defining and analyzing two types of helicoidal surfaces, using diffeomorphic transformations and criteria for cusps and cuspidal edges.
result Identification theorems for the singular types of both 1-type and 2-type helicoidal surfaces.

We define spin-c prequantization of a symplectic manifold to be a spin-c structure and a connection which are compatible with the symplectic form. We describe the cutting of an S^1-equivariant spin-c prequantization. The cutting process involves a choice of a spin-c prequantization for the complex plane. We prove that …

2007-10-23abs ↗pdf ↗

A symplectic cut of a manifold M with a Hamiltonian circle action is a symplectic quotient of M x C. If M is Kaehler then, since C is Kaehler, the cut space is Kaehler as well. The symplectic structure on the cut is well understood. In this paper we describe the complex structure (and hence the metric) on the cut. We t…

2002-12-04abs ↗pdf ↗

In this note, we study the cut locus of the free, step two Carnot groups Gk\mathbb{G}_k with kk generators, equipped with their left-invariant Carnot-Carathéodory metric. In particular, we disprove the conjectures on the shape of the cut loci proposed in [Myasnichenko - 2002] and [Montanari, Morbidelli - 2016], by exh…

2016-10-05abs ↗pdf ↗

Spectral Clustering as a relaxation of the normalized/ratio cut has become one of the standard graph-based clustering methods. Existing methods for the computation of multiple clusters, corresponding to a balanced kk-cut of the graph, are either based on greedy techniques or heuristics which have weak connection to th…

2015-05-24abs ↗pdf ↗

Spectral clustering is sensitive to how graphs are constructed from data particularly when proximal and imbalanced clusters are present. We show that Ratio-Cut (RCut) or normalized cut (NCut) objectives are not tailored to imbalanced data since they tend to emphasize cut sizes over cut values. We propose a graph partit…

2013-09-09abs ↗pdf ↗

This paper establishes the consistency of a family of graph-cut-based algorithms for clustering of data clouds. We consider point clouds obtained as samples of a ground-truth measure. We investigate approaches to clustering based on minimizing objective functionals defined on proximity graphs of the given sample. Our f…

2014-11-24abs ↗pdf ↗