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In spherical coordinates in N dimensions, with the parametrization x = rθ ∈ R N with r representing a positive real radius and θ an element of the unit sphere S N−1, = + + where Δ S N−1 is the Laplace–Beltrami operator on the (N − 1)-sphere, known as the spherical Laplacian.
The connection Laplacian, also known as the rough Laplacian, is a differential operator acting on the various tensor bundles of a manifold, defined in terms of a Riemannian- or pseudo-Riemannian metric. When applied to functions (i.e. tensors of rank 0), the connection Laplacian is often called the Laplace–Beltrami operator.
Let (t, ξ) be spherical coordinates on the sphere with respect to a particular point p of H n−1 (say, the center of the Poincaré disc). Here t represents the hyperbolic distance from p and ξ a parameter representing the choice of direction of the geodesic in S n−2. Then the hyperbolic Laplacian has the form:
Both are isotropic forms of discrete Laplacian, [8] and in the limit of small Δx, they all become equivalent, [11] as Oono-Puri being described as the optimally isotropic form of discretization, [8] displaying reduced overall error, [2] and Patra-Karttunen having been systematically derived by imposing conditions of rotational invariance, [9 ...
6.11 Hodge Laplacian on p-forms. ... Download as PDF; Printable version; ... An orthonormal inertial frame is a coordinate chart such that, ...
The Laplacian (also called tension field) is defined via the second fundamental form, and its vanishing is the condition for the map to be harmonic. The definitions extend without modification to the setting of pseudo-Riemannian manifolds .
In Cartesian coordinates, the divergence of a continuously differentiable vector field = + + is the scalar-valued function: = = (, , ) (, , ) = + +.. As the name implies, the divergence is a (local) measure of the degree to which vectors in the field diverge.
The random walk normalized Laplacian can also be called the left normalized Laplacian := + since the normalization is performed by multiplying the Laplacian by the normalization matrix + on the left. It has each row summing to zero since P = D + A {\displaystyle P=D^{+}A} is right stochastic , assuming all the weights are non-negative.
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