Question on n-dimensional space

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In summary: Therefore, the vectors are linearly dependent.In summary, to show that in n-dimensional space, any n+1 vectors are linearly dependent, we can choose a basis for the space and use the fact that every basis spans the entire space. By assuming that the vectors are linearly independent, we can show that this leads to a contradiction, thus proving that the vectors must be linearly dependent.
  • #1
arenaninja
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Homework Statement


Show that in n-dimensional space, any n+1 vectors are linearly dependent.

Ok... I actually know this is true, but I'm lost as to how to show it.


Homework Equations


Vectors are linearly independent if the only solution to [tex]\alpha_{1}|v_{1}>+\alpha_{2}|v_{2}>+...+\alpha_{n}|v_{n}>+\alpha_{n+1}|v_{n+1}>=|0>[/tex] is the trivial solution (where [tex]\alpha_{1}=...=\alpha_{n}=\alpha_{n+1}=0[/tex]).


The Attempt at a Solution


So far I'm only making a statement that each vector has n elements but there are n+1 unknowns, so if the vectors are in the vector space, then they must be linearly dependent.

Any suggestions to improve my answer would be greatly appreciated.
 
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  • #2
Choose a basis for the n-dimensional space, what would the (n+1)th vector look like?

Mat
 
  • #3
You need to use somewhere that your space is n-dimensional. What's your definition of an n-dimensional space

It's probably that there exists a basis of n elements, we need to use this somewhere. So let [tex] \{e_1,...,e_n\}[/tex] be a basis of your space. Since any basis spans the entire space, we can write every [tex] v_i [/tex] as

[tex] v_i=\sum_{j=1}^n{\beta_{i,j} e_i} [/tex]

Now, we assume that

[tex] \alpha_1 v_1+...+\alpha_{n+1} v_{n+1}=0 [/tex]

This is equivalent to saying that

[tex] \alpha_1 \sum_{j=1}^n{\beta_{1,j} e_i}+...+\alpha_{n+1}\sum_{j=1}^n{\beta_{n+1,j} e_i}=0 [/tex]

A little bit of algebra shows that

[tex] \left(\sum_{i=1}^{n+1}{\alpha_i \beta_{i,1}}\right)e_1+...+ \left(\sum_{i=1}^{n+1}{\alpha_i \beta_{i,n}}\right)e_n=0[/tex]

Now, we use that the basis is linearly independent. We get the following equations (with indeterminates the alpha_i

[tex] \left\{ \begin{array}{l}
\alpha_1 \beta_{1,1}+...+\alpha_{n+1} \beta_{n+1,1}=0\\
...\\
\alpha_1 \beta_{1,n}+...+\alpha_{n+1} \beta_{n+1,n}=0
\end{array}\right. [/tex]

This is a homogoneous system of n equations and n+1 indeterminates. Such a system only has the zero solution. So every alpha_i must be zero.
 

1) What is n-dimensional space?

N-dimensional space is a mathematical concept that refers to a space with n number of dimensions, where n is any positive integer. It is a generalization of the familiar three-dimensional space (length, width, and height) and can have any number of dimensions, including infinite.

2) How is n-dimensional space different from 3-dimensional space?

In n-dimensional space, there are n number of axes or directions, whereas in 3-dimensional space, there are only three axes (x, y, and z). This means that n-dimensional space can have more complex shapes and configurations compared to 3-dimensional space.

3) Can n-dimensional space be visualized?

It can be difficult to visualize n-dimensional space as it goes beyond our three-dimensional perception. However, mathematicians use various techniques such as projections and computer-generated images to help visualize n-dimensional space.

4) What is the significance of n-dimensional space in science?

N-dimensional space is used in various scientific fields, including physics, computer science, and statistics, to model and analyze complex systems. For example, in physics, n-dimensional space is used to understand the behavior of particles in quantum mechanics.

5) How is n-dimensional space relevant in everyday life?

N-dimensional space may seem abstract, but it has practical applications in our daily lives. For instance, GPS technology uses n-dimensional space to determine the location of a user on a three-dimensional earth. In computer graphics, n-dimensional space is used to create realistic 3D images and animations.

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