Vectors and covectors under change of coordinates

In summary, the conversation discusses computing directly in coordinates for a given vector and covector, and the resulting summation equation. It also brings up the question of what happens when considering another vector and the importance of coordinate transformations in these calculations.
  • #1
spaghetti3451
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Homework Statement



If ##\bf{v}## is a vector and ##\alpha## is a covector, compute directly in coordinates that ##\sum a_{i}^{V}v^{i}_{V}=\sum a_{i}^{U}v^{j}_{U}##.

What happens if ##\bf{w}## is another vector and one considers ##\sum v^{i}w^{i}##?

Homework Equations



The Attempt at a Solution



##\alpha(\bf{v})=\alpha(\bf{v})##

##\implies (a_{i}^{V}\ \sigma^{i}_{V})(v^{k}_{V}\ \vec{e}_{k}^{V})=(a_{j}^{U}\ \sigma^{j}_{U})( v^{l}_{U}\ \vec{e}_{l}^{U})##,

where the Einstein summation convention has used to sum over the ##i##, ##j##, ##k## and ##l## indices and the left-hand side uses the ##U## coordinate system and the right-hand side uses the ##V## coordinate system, so that

##\implies a_{i}^{V}\ v^{k}_{V}\ \sigma^{i}_{V}(\vec{e}_{k}^{V}) = a_{j}^{U}\ v^{l}_{U}\ \sigma^{j}_{U}(\vec{e}_{l}^{U})##

##\implies a_{i}^{V}\ v^{k}_{V}\ \delta^{i}_{k} = a_{j}^{U}\ v^{l}_{U}\ \delta^{j}_{l}##

##\implies a_{i}^{V}\ v^{i}_{V}\ = a_{j}^{U}\ v^{j}_{U}##For the second part, again using the Einstein summation convention,

##v^{i}w^{i}=v^{i}w_{j}\delta^{ji}=\langle \vec{v},\vec{w}\rangle## for ##g^{ij}=\delta^{ij}##.

Now, ##g^{ij}=\delta^{ij}## is true only for Cartesian coordinates in flat space, so that the metric changes under a coordinate transformation. Therefore, the transformation of ##v^{i}w^{i}## depends upon the specific change of coordinates.

What do you think?
 
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  • #2
The first part is good. In the second part, I think they want you to show that ##v^i w^i## is invariant under a change of basis. Also if you want to talk about curvilinear coordinates (more generally curved spaces a.k.a. manifolds), you should distinguish vectors from points, and then one usually considers vector fields. There is a reason why a linear algebra course will not have a chapter on curvilinear coordinates. Yet to study curvilinear coordinates (and more generally, manifolds), you need to know about vector spaces. Take as an example, ##\mathbb{R}^2##. If this is thought as a two dimensional vector space, we don't talk about coordinate systems (since we don't care about general coordinate transformations), instead we talk about basis. But when you start to think of the Euclidean plane as a two dimensional manifold (albeit a very simple one), then you talk about general coordinate systems.You probably should state in the problem statement what the ##U## and ##V## subscripts/superscripts actually mean. It is just nicer for the reader if you make it a habit to state what your symbols mean, right after you write them down. An exception to this is if there is a conventional notation that you expect the reader to know. However since, the notation you used is not a widely used convention, you should state it.
 

1. What is the difference between a vector and a covector?

A vector is a mathematical object that represents both magnitude and direction, while a covector is a linear function that assigns a scalar value to each vector. In other words, a vector can be thought of as a "directional quantity" while a covector can be thought of as a "measurement".

2. How does a vector change under a change of coordinates?

A vector's components will change under a change of coordinates, but the vector itself will remain the same. This means that the vector's magnitude and direction will not change, but its representation in terms of coordinates will.

3. How are covectors affected by a change of coordinates?

Covectors are affected differently than vectors under a change of coordinates. Instead of changing their components, covectors will transform according to the inverse of the coordinate transformation. This means that the covectors will change their representation, but their underlying function will remain the same.

4. What is the relationship between vectors and covectors?

Vectors and covectors are closely related, as they are dual concepts. This means that for every vector, there is a corresponding covector, and vice versa. The two are also connected through the dot product, where the dot product of a vector and a covector gives a scalar value.

5. How are vector and covector bases related?

The bases for vectors and covectors are related by the transpose of the basis transformation matrix. This means that if the vector basis is represented by a matrix A, then the covector basis is represented by the transpose of A. This allows for the transformation of both vectors and covectors between different coordinate systems.

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