Coordinate system vs ordered basis

In summary: A basis for a vector space is an ordered list of vectors that specifies the coordinates of every point in the space.
  • #1
ConfusedMonkey
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I have an issue with the definition of coordinate system in differential geometry vs the definition of coordinate system in linear algebra. The post is a bit long, but it's necessary so that I get my point across.

Let ##V## be an ##n##-dimensional normed space over the reals and equip ##V## with the topology that its norm induces. ##V## can be given a natural smooth structure, making it into a smooth ##n##-manifold. Now, let ##\{v_1, \dots, v_n\}## be an ordered basis for ##V##. Any ##p \in V## can be written as ##p = c^i v_i##, where we are using Einstein notation. This means that ##p## has the coordinate representation ##(c^1, \dots, c^n)##, relative to the given basis. This seems to define a coordinate system - not in the usual differential geometric sense, but if ##V = \mathbb{R}^n## then a basis gives us coordinate axes.

However, we also have the usual definition of a coordinate system about ##p##: The ordered pair ##(U, \varphi)## is a coordinate system about ##p## if ##U \ni p## and ##U## is open and ##\varphi## is a diffeomorphism onto some open subset of ##\mathbb{R}^n##. This allows us to naturally identify ##p## with ##(x^1(p), \dots, x^n(p))## where the ##x^i## are the local coordinates of ##\varphi##.

So it seems that the two definitions of coordinate systems above give us the same thing: a way to uniquely identify ##p## with a point of ##\mathbb{R}^n##, which is precisely what we want. However, the two definitions are not equivalent. Let me demonstrate:

Given that ##V## is a finite-dimensional vector space, I will make the usual identification of ##V## with ##T_p V## and just write ##V## instead. Similarly, even though ##p \in V##, it will also be used interchangeably as both an element of ##V## as well as ##T_p V##. Given a coordinate system ##(U, \varphi)##, it induces a coordinate basis at ##p##, and this is like a coordinate system in the first linear algebraic sense that I described. That's fine. In a differential geometric sense, ##p## is identified with ##(x^1(p), \dots, x^n(p))##. In a linear algebraic sense, we can write ##p = p^i \frac{\partial}{\partial x^i}## where ##p^i = p(x^i)##. The coordinate representation of ##p##, in the linear algebraic sense is then ##(p^1, \dots, p^n)## which is naturally identified with ##(x^1(p), \dots, x^n(p))##. So whether we are using the differential geometric or linear algebraic definition of coordinate system, we get the same identification ##p \leftrightarrow (x^1(p), \dots, x^n(p))##.

However, the two definitions gave the same identification only because we used a coordinate basis. From what I have previously read (I don't remember the source, but I am sure that you more knowledgeable posters will be aware of this), not every basis for ##V## is a coordinate basis. That is, there could be an ordered basis ##\{w_1, \dots, w_n\}## such that no coordinate chart induces it. This bothers me, because by giving an ordered basis ##\{w_1, \dots, w_n\}##, we indeed do have a coordinate system - every element of ##V## has a coordinate representation relative to the basis, BUT, this basis may not necessarily give rise to a coordinate chart. So now we have a coordinate system in one sense (the linear algebraic) but we do not have an equivalent coordinate system in the differential geometric sense. This bothers me a lot!

The differential geometric definition of coordinate system was conceived of for when there is no natural or useful linear algebraic definition of coordinate system: That is, for when we cannot identify a manifold with its tangent space. But in the case when the manifold is a finite dimensional normed space, we can identify the manifold with its tangent space (for example, ##\mathbb{R}^n \leftrightarrow T_p \mathbb{R}^n##), and so in this case, both definitions should be equivalent, i.e. give the same coordinate system, but they do not, as I just demonstrated. How do I reconcile this?
 
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  • #2
To be honest, I don't get your point. You have ##\mathbb{R}^n## as manifold, which you call ##V##, ##\mathbb{R}^n## as tangent space ##T_p(V)## and ##\mathbb{R}^n## as Euclidean space where the charts are from. So all of your basis are those of ##\mathbb{R}^n## and you get different representations: ##(c^1,\ldots , c^n)\, , \,(x^1(p),\ldots ,x^n(p))\, , \,(p^1,\ldots ,p^n)## and whatever the coordinates according to ##\{w_1,\ldots ,w_n\}## are. The basis ##\{\frac{\partial}{\partial x^1},\ldots ,\frac{\partial}{\partial x^n}\}## is a orthogonal basis, the others any. Fine until here. Then you write
ConfusedMonkey said:
From what I have previously read (I don't remember the source, but I am sure that you more knowledgeable posters will be aware of this), not every basis for ##V## is a coordinate basis.´
What should this mean? What is a coordinate basis? And "I have previously read" is a miserable source.
That is, there could be an ordered basis ##\{w_1, \dots, w_n\}## such that no coordinate chart induces it.
What does "induces it" mean? If you have a basis of a vector space, then the coordinates are the components according to this basis. If you have a manifold, then basis means either one of the tangent space or one of the chart map. The rest are basis transformations, as you always have ##\mathbb{R}^n## everywhere in your example.

The only interesting point is, that the basis vectors of the tangent space above are the directional derivatives of the standard basis in ##\mathbb{R}^n## which makes the notation a bit different than usual.
ConfusedMonkey said:
this basis may not necessarily give rise to a coordinate chart
A basis gives rise to a chart map? A chart maps a part of the manifold on a part of a Euclidean space which has a basis. What did you mean by the first basis you mentioned? If you have a different basis in the tangent space than for your charts, you also have a basis transformation. So what? If you have a basis in your manifold, which only makes sense in an example as the one above, where the manifold itself is a Euclidean space, then you can have again a different basis than the one for the charts. However, since all vector spaces here: ##V,T_p(V),\mathbb{R}^n## are the same, I would chose only one basis for all of them: ##(x^i) \textrm{ in }V \, , \,(\frac{\partial}{\partial x^i}) \textrm{ in }T_p(V)\, , \,(\mathfrak{e}^i)\textrm{ in }\mathbb{R}^n## are noted differently but are basically all the same.
 
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  • #3
fresh_42 said:
What should this mean? What is a coordinate basis? And "I have previously read" is a miserable source.

A coordinate basis is a basis for the tangent space which is induced by the coordinate chart. For example, if ##(U, \varphi)## is a coordinate chart for a smooth manifold ##M## containing a point ##p##, where ##\varphi = (x^1, \dots, x^n)##, then the coordinate basis for ##T_p M## induced by this chart is ##\{\frac{\partial}{\partial x^i}, \dots, \frac{\partial}{\partial x^n}\}##.

Here is a source. See post #6: https://www.physicsforums.com/threads/classifications-of-basis-vectors.785676/

Also, I asked the same question here: https://math.stackexchange.com/questions/2299345/coordinate-system-vs-ordered-basis
and was told: "At a single, fixed point, any basis comes from a coordinate chart. But, yes, if you look at a (smooth) choice of basis throughout an open set, it'll only come from a coordinate chart if the pairwise Lie brackets ##[w_i,w_j]## all vanish."

Anyway, my initial post may have been too long winded, obscuring my point. Let me try again.

If we are in a finite dimensional vector space, then any ordered basis ##\{v_1, \dots, v_n\}## is a coordinate system, because for any ##p \in V## we can write ##p = c^i v_i## and so the coordinate representation of ##p## is ##(c^1, \dots, c^n)##.

Now suppose we are in a general topological space. In general, it isn't a vector space and so we cannot just impose a coordinate system on the manifold by using a basis. However, what we can do is equip the topological space with local coordinate charts, making it into a manifold.

So we have two definitions of coordinate systems. One that uses basis vectors, and one that uses coordinate charts. But, there are cases, such as ##\mathbb{R}^n## where we could use both definitions of "coordinate systems". We could use basis vectors to define a coordinate system or we could use smooth coordinate charts. However, the two definitions are not equivalent because while every coordinate chart gives a basis for ##\mathbb{R}^n## (we are still using the identification ##\mathbb{R}^n \leftrightarrow T_p \mathbb{R}^n##), not every basis for ##\mathbb{R}^n## has a corresponding coordinate chart. So if I wanted a coordinate chart on ##\mathbb{R}^n##, which definition do I use? That is what I am confused about - the fact that there are slightly differing notions for "coordinate system" in the case of ##\mathbb{R}^n##, or in the slightly more general case where the manifold is a finite-dimensional normed space.
 
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  • #4
You seem to have several confusions. Let us try to clear them up.
ConfusedMonkey said:
If we are in a finite dimensional vector space, then any ordered basis ##\{v_1, \dots, v_n\}## is a coordinate system, because for any ##p \in V## we can write ##p = c^i v_i## and so the coordinate representation of ##p## is ##(c^1, \dots, c^n)##.

An ordered basis is not a coordinate system. However, it defines a coordinate system on the vector space where the coordinates are taken to be the components of a vector with respect to the ordered basis. Note that this will give you an affine coordinate system, which is only a subset of the possible coordinate systems. There is no reason to expect an arbitrary coordinate system to be affine.

Now suppose we are in a general topological space. In general, it isn't a vector space and so we cannot just impose a coordinate system on the manifold by using a basis. However, what we can do is equip the topological space with local coordinate charts, making it into a manifold.

You need a topological space that is locally homeomorphic to ##\mathbb R^n##. Just any topological space will not do.

So we have two definitions of coordinate systems. One that uses basis vectors, and one that uses coordinate charts.

As I said earlier, your first definition defines an affine coordinate system, it is not the most general type of coordinate system.

But, there are cases, such as ##\mathbb{R}^n## where we could use both definitions of "coordinate systems". We could use basis vectors to define a coordinate system or we could use smooth coordinate charts. However, the two definitions are not equivalent because while every coordinate chart gives a basis for ##\mathbb{R}^n## (we are still using the identification ##\mathbb{R}^n \leftrightarrow T_p \mathbb{R}^n##), not every basis for ##\mathbb{R}^n## has a corresponding coordinate chart.
You are contradicting yourself here. Every vector basis in a vector space does give a corresponding affine coordinate system. Note that the set of basis vectors for a (non-affine) coordinate system changes from point to point. For example, in spherical coordinates the position vector is ##r\vec e_r## everywhere because ##\vec e_r## depends on the position.

So if I wanted a coordinate chart on ##\mathbb{R}^n##, which definition do I use? That is what I am confused about - the fact that there are slightly differing notions for "coordinate system" in the case of ##\mathbb{R}^n##, or in the slightly more general case where the manifold is a finite-dimensional normed space.
There is only one definition of a coordinate chart, it needs to locally uniquely specify a point in the manifold. An affine coordinate system is a type of coordinate system (which includes the subset of Cartesian coordinates when the basis is orthonormal), not all coordinate systems are affine.
 
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  • #5
I guess I will just have to live with the fact that not every ordered basis for Euclidean space will be a coordinate basis, and whether I use a linear algebraic or differential geometric coordinate system will depend on the case at hand.

EDIT: I posted this at the same time you replied, Orodruin. I will read your post then reply to it some time tomorrow as it is very late where I am.
 
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  • #6
I'm not sure whether it's appropriate entering into this discussion, but I'm following this thread since the opener started it. I have a question.
Orodruin said:
An ordered basis is not a coordinate system. However, it defines a coordinate system on the vector space where the coordinates are taken to be the components of a vector with respect to the ordered basis
What you mean here? e.g. in ##\mathbb{R}^3##, take a point ##p## with coordinates ##(x,y,z)##; if a vector has components ##(x,y,z)##, then the ordered basis ##(1,0,0), (0,1,0),(0,0,1)## defines an affine coordinate system at ##p##?
 
  • #7
davidge said:
I'm not sure whether it's appropriate entering into this discussion, but I'm following this thread since the opener started it. I have a question.

What you mean here? e.g. in ##\mathbb{R}^3##, take a point ##p## with coordinates ##(x,y,z)##; if a vector has components ##(x,y,z)##, then the ordered basis ##(1,0,0), (0,1,0),(0,0,1)## defines an affine coordinate system at ##p##?
Given an ordered basis (it does not need to be orthonormal) ##\vec w_i## in a vector space, you can use the ##n##-tuple of numbers ##\zeta^i## as coordinates such that an element in the vector space is written ##\vec v = \zeta^i w_i##. The basis itself is a basis, not a coordinate system.
 
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  • #8
@Orodruin

Yes, a basis is a basis and only defines a coordinate system, I was speaking loosely, which is not a good thing in mathematics. I have realized where I was going wrong. A basis ##\{v_i\}## for ##V## determines a smooth global chart, ##(V, \varphi)## on ##V## and this chart determines a global frame of coordinate vector fields on ##TV##. However, the key is that not every frame will be determined by a coordinate chart.
 

What is the difference between a coordinate system and an ordered basis?

A coordinate system is a set of rules and conventions used to specify the location of points in space. It typically includes a set of axes and a unit of measurement. An ordered basis, on the other hand, is a set of vectors that form a basis for a vector space. These vectors can be used to represent other vectors in the space through linear combinations.

How are coordinate systems and ordered bases related?

Coordinate systems and ordered bases are closely related, as they both provide a way to represent points and vectors in a space. In fact, a coordinate system can be thought of as a specific type of ordered basis, where the basis vectors are aligned with the axes of the coordinate system. However, not all ordered bases can be used as coordinate systems, as they may not have the necessary properties to represent points in a unique and consistent manner.

Can a coordinate system and ordered basis be used interchangeably?

While coordinate systems and ordered bases serve similar purposes, they are not interchangeable. A coordinate system is a specific type of ordered basis that is used to represent points in space, while an ordered basis can represent any vector in a vector space. Additionally, coordinate systems often have additional rules and conventions, such as orientation and scaling, that are not necessarily present in ordered bases.

How do you choose a coordinate system or ordered basis?

The choice of coordinate system or ordered basis depends on the specific problem or application at hand. For example, in 2D space, a Cartesian coordinate system may be a good choice for representing points, while a polar coordinate system may be more suitable for representing vectors. In general, the choice should be made based on what is most convenient and intuitive for the problem at hand.

Are there different types of coordinate systems and ordered bases?

Yes, there are many different types of coordinate systems and ordered bases that can be used depending on the needs of the problem. Some common examples include Cartesian coordinates, polar coordinates, spherical coordinates, and cylindrical coordinates. Similarly, there are different types of ordered bases, such as standard bases, orthogonal bases, and orthonormal bases. The choice of which type to use depends on the specific problem and the properties that are required.

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