2013
DOI: 10.1007/978-3-642-40020-9_39
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An Extrinsic Look at the Riemannian Hessian

Abstract: Let f be a real-valued function on a Riemannian submanifold of a Euclidean space, and letf be a local extension of f . We show that the Riemannian Hessian of f can be conveniently obtained from the Euclidean gradient and Hessian off by means of two manifoldspecific objects: the orthogonal projector onto the tangent space and the Weingarten map. Expressions for the Weingarten map are provided on various specific submanifolds.

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Cited by 75 publications
(98 citation statements)
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“…We will show that G(·) and H(·) are Riemannian gradient and Riemannian Hessian of f over Ω in the following lemma. A similar argument can be found in [17] and [18] Lemma 5. G(·) and H(·) defined in 3.2 and 3.3 are the Riemannian gradient and Riemannian Hessian of f (·) over Ω.…”
Section: Riemannian Gradient and Riemannian Hessiansupporting
confidence: 77%
“…We will show that G(·) and H(·) are Riemannian gradient and Riemannian Hessian of f over Ω in the following lemma. A similar argument can be found in [17] and [18] Lemma 5. G(·) and H(·) defined in 3.2 and 3.3 are the Riemannian gradient and Riemannian Hessian of f (·) over Ω.…”
Section: Riemannian Gradient and Riemannian Hessiansupporting
confidence: 77%
“…13, the covariant second derivatives, valid at all points of the phase space, can be calculated using a projector-based approach. 64 The corresponding 2N × 2N Hessian matrix can be represented as…”
Section: F Minimum Mode Following Methodsmentioning
confidence: 99%
“…In this larger space, second order derivatives are easily performed. The Hessian in the physical subspace can then be reconstructed by a projection operator approach [28]. For any scalar function f on the manifold M phys , this true Hessian is defined as…”
mentioning
confidence: 99%