Computing tangent spaces of implicitly defined manifolds

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To find the tangent space at a specific point on an implicitly defined manifold given by f(x) = c, the gradient of the function f is crucial, as it is perpendicular to the tangent space. The relationship can be expressed as grad f(x) · v = 0, where v represents a vector in the tangent space. While explicit parametrization and Jacobian computation can be useful, the gradient approach provides a direct method for determining tangent vectors. Implicit differentiation may also offer additional insights, although specific techniques were not detailed in the discussion. Understanding these concepts is essential for effectively analyzing tangent spaces in implicit manifolds.
sin123
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Hi there,

Is there an "easy" way to find a tangent space at a specific point to an implicitly defined manifold? I am thinking of a manifold defined by all points x in R^k satisfying f(x) = c for some c in R^m. Sometimes I can find an explicit parametrization and compute the Jacobian matrix, sometimes I can compute the normal vector to the manifold (when c is just a real number), but that's where I am running out of ideas. I am hoping that there might be some sort of implicit differentiation trick that I have not figured out yet.
 
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sin123 said:
Hi there,

Is there an "easy" way to find a tangent space at a specific point to an implicitly defined manifold? I am thinking of a manifold defined by all points x in R^k satisfying f(x) = c for some c in R^m. Sometimes I can find an explicit parametrization and compute the Jacobian matrix, sometimes I can compute the normal vector to the manifold (when c is just a real number), but that's where I am running out of ideas. I am hoping that there might be some sort of implicit differentiation trick that I have not figured out yet.

i am not sure if I am telling you something that you already know but the gradient of f is perpendicular to the tangent space of f(x) = c. So the equation for it is gradf(x).v = 0
 

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