3,402 research outputs found
Surface Networks
We study data-driven representations for three-dimensional triangle meshes,
which are one of the prevalent objects used to represent 3D geometry. Recent
works have developed models that exploit the intrinsic geometry of manifolds
and graphs, namely the Graph Neural Networks (GNNs) and its spectral variants,
which learn from the local metric tensor via the Laplacian operator. Despite
offering excellent sample complexity and built-in invariances, intrinsic
geometry alone is invariant to isometric deformations, making it unsuitable for
many applications. To overcome this limitation, we propose several upgrades to
GNNs to leverage extrinsic differential geometry properties of
three-dimensional surfaces, increasing its modeling power.
In particular, we propose to exploit the Dirac operator, whose spectrum
detects principal curvature directions --- this is in stark contrast with the
classical Laplace operator, which directly measures mean curvature. We coin the
resulting models \emph{Surface Networks (SN)}. We prove that these models
define shape representations that are stable to deformation and to
discretization, and we demonstrate the efficiency and versatility of SNs on two
challenging tasks: temporal prediction of mesh deformations under non-linear
dynamics and generative models using a variational autoencoder framework with
encoders/decoders given by SNs
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Rapid coastal deoxygenation due to ocean circulation shift in the NW Atlantic.
Global observations show that the ocean lost approximately 2% of its oxygen inventory over the last five decades 1-3, with important implications for marine ecosystems 4, 5. The rate of change varies with northwest Atlantic coastal waters showing a long-term drop 6, 7 that vastly outpaces the global and North Atlantic basin mean deoxygenation rates 5, 8. However, past work has been unable to resolve mechanisms of large-scale climate forcing from local processes. Here, we use hydrographic evidence to show a Labrador Current retreat is playing a key role in the deoxygenation on the northwest Atlantic shelf. A high-resolution global coupled climate-biogeochemistry model 9 reproduces the observed decline of saturation oxygen concentrations in the region, driven by a retreat of the equatorward-flowing Labrador Current and an associated shift toward more oxygen-poor subtropical waters on the shelf. The dynamical changes underlying the shift in shelf water properties are correlated with a slowdown in the simulated Atlantic Meridional Overturning Circulation 10. Our results provide strong evidence that a major, centennial-scale change of the Labrador Current is underway, and highlight the potential for ocean dynamics to impact coastal deoxygenation over the coming century
Nonlinear polarization dynamics of Kerr beam self-cleaning in a GRIN multimode optical fiber
We experimentally study polarization dynamics of Kerr beam self-cleaning in a
graded-index multimode optical fiber. We show that spatial beam cleaning is
accompanied by nonlinear polarization rotation, and a substantial increase of
the degree of linear polarization.Comment: 5 pages, 6 figure
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