Describing vectors in n dimensions

In summary, A can be broken up into its components x,y, and z, and for a four-dimensional vector, it can have as many components as there are dimensions. The symbol ⋯ indicates a sequence and in the notation A=A_x\widehat{i}+A_y\widehat{j}+A_z\widehat{k}+...A_n\widehat{t}, the components are relative to a basis.
  • #1
Nano-Passion
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Recall that A can be broken up into its components x,y, and z. Can You simply add more components to describe any number of dimensions. Where n would be nth dimension?

A=A_x+ A_y+A_z+⋯A_n
 
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  • #2
What's the square symbol for? And why do you have theoretical physics degree in your status thingy? Do you mean you will someday hope to get such a degree? I'm hoping of doing a theoretical phd someday. I didn't know there was such a thing as a purely theoretical undergraduate degree, if that's what youre talking about?

About the question: If we have a vector A, then it can be written (in some basis) as its components (A1,A2,A3,A4) For a four-dimensional vector, so yeah, there are as many components as there are dimensions.
 
  • #3
BruceW said:
What's the square symbol for? And why do you have theoretical physics degree in your status thingy? Do you mean you will someday hope to get such a degree? I'm hoping of doing a theoretical phd someday. I didn't know there was such a thing as a purely theoretical undergraduate degree, if that's what youre talking about?

About the question: If we have a vector A, then it can be written (in some basis) as its components (A1,A2,A3,A4) For a four-dimensional vector, so yeah, there are as many components as there are dimensions.

For PhD I wrote what I'm striving for. Perhaps that isn't what I should do. :devil: I'll edit it.

I've only begun my third semester. :)

Edit: What square symbol?
 
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  • #4
A=A_x+ A_y+A_z+⋯A_n
The symbol ⋯ just before A_n it looks like two horizontal lines..
 
  • #5
BruceW said:
A=A_x+ A_y+A_z+⋯A_n
The symbol ⋯ just before A_n it looks like two horizontal lines..

Oh sorry, that is supposed to be an ellipse (...) that indicates the sequence.
 
  • #6
You don't write it that way. The components are relative to a basis as Bruce mentioned. A vector can be represented as a linear combination of components relative to said basis vectors so it would be written compactly as [itex]V = V^{\alpha }\vec{e}_{\alpha }[/itex] where the repeated indices imply summation over all possible values the index can take. So, for example, a vector [itex]V \in \mathbb{R}^{n}[/itex] can be written, when equipped with the Cartesian chart, as [itex]V = V^{x}\vec{e_{x}} + ... + V^{n}\vec{e_{n}}[/itex] where [itex]\vec{e_{x}} = (1, 0, ..., 0)[/itex] and similarly for the other basis vectors.
 
  • #7
WannabeNewton said:
You don't write it that way. The components are relative to a basis as Bruce mentioned. A vector can be represented as a linear combination of components relative to said basis vectors so it would be written compactly as [itex]V = V^{\alpha }\vec{e}_{\alpha }[/itex] where the repeated indices imply summation over all possible values the index can take. So, for example, a vector [itex]V \in \mathbb{R}^{n}[/itex] can be written, when equipped with the Cartesian chart, as [itex]V = V^{x}\vec{e_{x}} + ... + V^{n}\vec{e_{n}}[/itex] where [itex]\vec{e_{x}} = (1, 0, ..., 0)[/itex] and similarly for the other basis vectors.

I have to admit, I am not familiar with that notation. But I will mention that my book stated [itex]A=A_x\widehat{i}+A_y\widehat{j}+A_z\widehat{k}[/itex]. Which is why I simply put:

[itex] A=A_x\widehat{i}+A_y\widehat{j}+A_z\widehat{k}+...A_n\widehat{t}[/itex]
 
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  • #8
Nano-Passion said:
I have to admit, I am not familiar with that notation. But I will mention that my book stated [itex]A=A_x\widehat{i}+A_y\widehat{j}+A_z\widehat{k}[/itex]. Which is why I simply put:

[itex] A=A_x\widehat{i}+A_y\widehat{j}+A_z\widehat{k}+...A_n\widehat{t}[/itex]

No that is perfectly correct. It just wasn't in your original post is all.
 

FAQ: Describing vectors in n dimensions

What is a vector in n dimensions?

A vector in n dimensions is a mathematical quantity that represents a magnitude and direction in a space with n dimensions. It is typically represented as an ordered list of n numbers, and is used to describe the movement or position of a point in n-dimensional space.

How is a vector in n dimensions different from a regular vector?

A vector in n dimensions is similar to a regular vector in that it has a magnitude and direction, but it exists in a space with n dimensions instead of just two or three. This means that it can represent more complex movements or positions in higher dimensional spaces.

How do you describe a vector in n dimensions?

A vector in n dimensions can be described using its magnitude and direction, which can be represented using mathematical equations or geometric diagrams. It can also be described as an ordered list of n numbers, with each number representing the magnitude in a specific dimension.

What are some real-world applications of vectors in n dimensions?

Vectors in n dimensions have many applications in fields such as physics, engineering, and computer science. They can be used to describe the motion of objects in space, model complex physical systems, and represent data in high-dimensional spaces for machine learning algorithms.

How do you perform operations on vectors in n dimensions?

Operations on vectors in n dimensions are similar to regular vector operations, but they involve working with multiple dimensions. Addition, subtraction, and scalar multiplication can be performed using mathematical equations, while dot products and cross products can be used to calculate angles and determine orthogonality.

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