Is Symmetry Present in the Derivatives of Normal Vectors on Surfaces?

In summary, the conversation discusses the derivative of the normalised normal vector to a surface in n-dimensional Euclid space. It is mentioned that in Cartesian coordinates, the equation \frac{\partial n_j}{\partial x^i} = \frac{\partial n_i}{\partial x^j} is correct. The conversation also touches on finding acceleration and reformulating the task in the language of differential geometry, as well as the symmetry of the second term in the equation.
  • #1
rych
2
0
Are there any facts about the derivative of the normalised normal vector n to a surface embedded in n-dimensional Euclid space? Is it true, for instance, that
[tex]\frac{\partial n_j}{\partial x^i} = \frac{\partial n_i}{\partial x^j}[/tex]
The context is as follows. The surface is defined implicitly by a constraint function; there's a Hamiltonian in reduntant coordinates and the canonical Hamiltonian equations of motion for (q,p) ensuring that trajectories lie in the constraint surface. I need to find acceleration [itex]\ddot{q}[/itex]; there the time derivative of n appears. By the way, how could I reformulate this task in the language of differential geometry?
 
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  • #2
If the surface is given by [itex]\phi (\vec{r})=const.[/itex] then the normal to the surface is [itex]n_i=(\vec{\nabla}\phi)_i[/itex], it's not necessarilly unit normal, but this is easily reconciled. So, in Cartesian coordinates

[tex]\frac{\partial n_j}{\partial x^i} = \frac{\partial n_i}{\partial x^j}[/tex]

is correct.
 
Last edited:
  • #3
[tex]\frac{\partial n_j}{\partial x^i} = \partial_i \frac{\partial_j \phi}{(\nabla \phi \cdot \nabla \phi)^\frac{1}{2}} = \frac{\partial_{ij}\phi}{(\nabla \phi \cdot \nabla \phi)^\frac{1}{2}} - \frac{\partial_j \phi \sum_k \partial_k \phi \partial_{ik}\phi}{(\nabla \phi \cdot \nabla \phi)^{\frac{3}{2}}}[/tex]

Thanks for the response! But I can't easily reconcile the second term: it doesn't seem to be symmetric.
 
  • #4
rych said:
[tex]\frac{\partial n_j}{\partial x^i} = \partial_i \frac{\partial_j \phi}{(\nabla \phi \cdot \nabla \phi)^\frac{1}{2}} = \frac{\partial_{ij}\phi}{(\nabla \phi \cdot \nabla \phi)^\frac{1}{2}} - \frac{\partial_j \phi \sum_k \partial_k \phi \partial_{ik}\phi}{(\nabla \phi \cdot \nabla \phi)^{\frac{3}{2}}}[/tex]

Thanks for the response! But I can't easily reconcile the second term: it doesn't seem to be symmetric.

It's not, ignore me when I put the bit about "reconcilitation", I didn't mean to put that.
 

Related to Is Symmetry Present in the Derivatives of Normal Vectors on Surfaces?

What is a normal vector?

A normal vector is a vector that is perpendicular to a surface or curve at a specific point.

What is the differential of a normal vector?

The differential of a normal vector is a vector that describes the change in the normal vector at a specific point on a surface or curve.

How is the differential of a normal vector calculated?

The differential of a normal vector can be calculated using the partial derivatives of the surface or curve's equation with respect to each of its parameters.

What is the significance of the differential of a normal vector?

The differential of a normal vector is important in differential geometry and calculus, as it allows for the calculation of important properties such as curvature and surface area.

How does the differential of a normal vector relate to the curvature of a surface or curve?

The magnitude of the differential of a normal vector is directly related to the curvature of a surface or curve at a specific point. A larger differential indicates a greater curvature, while a smaller differential indicates a flatter surface or curve.

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