Vector components and its coordinate description in a given basis

In summary: For example, it is possible to define a "vector space" whose elements are functions, say ##f(x)##, and whose "addition" operation is the pointwise addition of functions, ##f(x)+g(x)##, and whose "scalar multiplication" operation is multiplication of the function by a scalar, ##\lambda f(x)##. So, in this "vector space" a "vector" is a function, and the "coordinates" of the "vector" relative to the "basis" {1, x, x^2, x^3, ...} are the functions ##f_0(x)=1##, ##f_1(x)=x##, ##f_2(x)=x
  • #1
"Don't panic!"
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Given a basis [itex]\mathfrak{B}=\lbrace\mathbf{e}_{i}\rbrace[/itex] it is possible to represent a vector [itex]\mathbf{v}[/itex] as a column vector

[itex]\left[\mathbf{v}\right]_{\mathfrak{B}}= \left(\begin{matrix}v^{1} \\ v^{2} \\ \vdots \\ v^{n}\end{matrix}\right)[/itex]

where the [itex]v_{i}[/itex] are the components of [itex]\mathbf{v}[/itex] relative to the basis [itex]\mathfrak{B}[/itex].

I understand that the components, [itex]v_{i}[/itex] correspond to the projection of [itex]\mathbf{v}[/itex] onto each basis vector, [itex]\mathbf{e}_{i}[/itex], but is it correct to say that we can consider them as coordinates of [itex]\mathbf{v}[/itex] relative to [itex]\mathfrak{B}[/itex] (where the [itex]\mathbf{e}_{i}[/itex] define the coordinate axes of the given basis), due to the fact that it is always possible to represent any set of basis vectors in the basis that they define, such that the resulting column vectors will `look like' the standard basis?
Or can one only talk about 'coordinates' of a vector relative to a given basis if that basis is 'ordered'?Sorry if this is wildly wrong, just starting to get the 'hang' (a bit) of the concept of abstract vector spaces, but still struggling to move away from the specific case of "physical" vectors in Euclidean space.
 
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  • #2
What do you mean when you say a basis is "ordered"? The answer to your first question is yes.
 
  • #3
mathman said:
What do you mean when you say a basis is "ordered"? The answer to your first question is yes.

Thanks.

By "ordered" I mean that there is a specific order to the elements of a given basis, such that rearranging any of the elements in a given basis results in a new (distinct) basis?!
 
  • #4
"Don't panic!" said:
Thanks.

By "ordered" I mean that there is a specific order to the elements of a given basis, such that rearranging any of the elements in a given basis results in a new (distinct) basis?!
Define ##\mathfrak{B}'=\{\mathbf{e}_j'\}## as a basis, with ##\mathbf{e}_i'=\mathbf{e}_{n-i+1}##.

Then, ##\mathfrak{B}=\mathfrak{B}'##. I suspect you're thinking of "ordered pairs." As it turns out, we can order them for convenience, but the fact remains that vector spaces are abelian groups under addition, so ##\mathbf{e}_1+\mathbf{e}_2=\mathbf{e}_2+\mathbf{e}_1##.

Our notation with vectors in columns and rows acts like a function, sending an element of a field in an entry to a corresponding (predetermined) basis vector scalar-multiplied by that field element. Thus, when we talk of coordinates, we ARE talking about ordered sets.
 
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  • #5
Mandelbroth said:
Define ##\mathfrak{B}'=\{\mathbf{e}_j'\}## as a basis, with ##\mathbf{e}_i'=\mathbf{e}_{n-i+1}##.

Then, ##\mathfrak{B}=\mathfrak{B}'##. I suspect you're thinking of "ordered pairs." As it turns out, we can order them for convenience, but the fact remains that vector spaces are abelian groups under addition, so ##\mathbf{e}_1+\mathbf{e}_2=\mathbf{e}_2+\mathbf{e}_1##.

Our notation with vectors in columns and rows acts like a function, sending an element of a field in an entry to a corresponding (predetermined) basis vector scalar-multiplied by that field element. Thus, when we talk of coordinates, we ARE talking about ordered sets.

So is it correct then to say that the reason why we can consider the components of a vector as coordinates of that vector relative to a given basis because of the fact that it is always possible to represent any set of basis vectors in the basis that they define, such that the resulting column vectors will `look like' the standard basis? In this sense, is it correct to say the the elements of a given basis define a coordinate system, with each basis vector defining a particular coordinate axis within that system?
 
  • #6
An ordered basis is the exact termination my linear algebra book uses, it is just a basis regarded as a sequence rather than a set of linearly dependent, space-generating vectors.

Just throwing that out there. I thought the term was common. I don't see how the concept isn't required, and I think the answer to the OP's question "can one only talk about 'coordinates' of a vector relative to a given basis if that basis is 'ordered'?" is yes.
 
  • #7
1MileCrash said:
I don't see how the concept isn't required, and I think the answer to the OP's question "can one only talk about 'coordinates' of a vector relative to a given basis if that basis is 'ordered'?" is yes.

You can only use vector or matrix notation to do numerical calculations in linear algebra, using some specified ordered basis.

But there is a lot more to the mathematics of linear algebra than "vectors and matrices whose elements are real or complex numbers".
 

1. What are vector components?

Vector components refer to the individual parts or elements that make up a vector. They can be thought of as the projections of a vector onto each coordinate axis.

2. What is a coordinate description of a vector?

A coordinate description of a vector is a way of representing a vector using its components in a specific coordinate system or basis. It includes the magnitude and direction of the vector as well as the values of its components along each coordinate axis.

3. How do you find vector components?

To find the components of a vector, you can use the dot product or projection methods. The dot product method involves multiplying the vector with the unit vectors along each coordinate axis. The projection method involves finding the projection of the vector onto each coordinate axis using trigonometry.

4. What is a basis in vector components?

A basis is a set of linearly independent vectors that span a vector space. In the context of vector components, it refers to the set of coordinate axes that are used to describe a vector. The most common basis is the standard basis, which uses the x, y, and z axes.

5. Why is it important to use a given basis in vector components?

Using a given basis in vector components allows for a standardized and consistent way of representing vectors. It also makes it easier to perform calculations and compare vectors in the same coordinate system. Additionally, using different bases can provide different perspectives and insights into the properties of a vector.

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