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Bibliographic Details
Main Author: Liu, Daoqiang
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2307.07278
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author Liu, Daoqiang
author_facet Liu, Daoqiang
contents In this paper, we prove the long neck principle, band width estimates, and width inequalities of the geodesic collar neighborhoods of the boundary in the setting of general initial data sets for the Einstein equations, subject to certain energy conditions corresponding to the lower bounds of scalar curvature on Riemannian manifolds. Our results are established via the spinorial Callias operator approach.
format Preprint
id arxiv_https___arxiv_org_abs_2307_07278
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle On the long neck principle and width estimates for initial data sets
Liu, Daoqiang
Differential Geometry
In this paper, we prove the long neck principle, band width estimates, and width inequalities of the geodesic collar neighborhoods of the boundary in the setting of general initial data sets for the Einstein equations, subject to certain energy conditions corresponding to the lower bounds of scalar curvature on Riemannian manifolds. Our results are established via the spinorial Callias operator approach.
title On the long neck principle and width estimates for initial data sets
topic Differential Geometry
url https://arxiv.org/abs/2307.07278