How to prove that the dim of two subspaces added together equals dim

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In summary, the dim of two subspaces added together equals the dim of their union plus 1 iff one space is a subspace of the other. This is a standard result that should be in just about any linear algebra textbook.
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gutnedawg
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How to prove that the dim of two subspaces added together equals dim of their union plus 1 iff one space is a subest of the other

In other words,
subspaces: V, S of Vector space: W

[tex] dim(V+S) = dim(V \cap S) +1 [/tex]

if [tex]V \subseteq S[/tex] or [tex]S \subseteq V [/tex]
 
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  • #2


I don't think this is true. If V=S then arent V+S and V intersect S the same?
 
  • #3


eok20 is correct, the statement is false.

What is true is

[tex]dim(V+S) = dim(V) + dim(S) - dim(V \cap S)[/tex]

which reduces to a simpler form if [itex]V \subseteq S[/itex] or [itex]S \subseteq V[/itex].
 
  • #4


eok20 said:
I don't think this is true. If V=S then arent V+S and V intersect S the same?

perhaps I mistyped the question.
[tex] dim(V+S) = dim(V \cap S) +1 [/tex] is given for these subspaces.

One has to prove that

[tex] V \subseteq S [/tex] or [tex] S \subseteq V [/tex]
 
  • #5


gutnedawg said:
perhaps I mistyped the question.
[tex] dim(V+S) = dim(V \cap S) +1 [/tex] is given for these subspaces.

One has to prove that

[tex] V \subseteq S [/tex] or [tex] S \subseteq V [/tex]

OK, suppose

[tex]V \not\subseteq S[/tex] and [tex]S \not\subseteq V[/tex].

Then V contains at least one element not in S, hence at least one element not in [itex]V \cap S[/itex]. Thus [itex]dim(V) > dim(V \cap S)[/itex], and since dimensions are integers, this is the same as [itex]dim(V) \geq dim(V \cap S) + 1[/itex].

Similarly, S contains at least one element not in V, so [itex]dim(S) \geq dim(V \cap S) + 1[/itex].

Now apply those inequalities to

[tex]dim(V+S) = dim(V) + dim(S) - dim(V \cap S)[/tex]

to achieve a contradiction.
 
  • #6


How do I come to the fact that

[tex] dim(V+S) = dim(V) + dim(S) - dim( V \cap S) [/tex]


jbunniii said:
OK, suppose

[tex]V \not\subseteq S[/tex] and [tex]S \not\subseteq V[/tex].

Then V contains at least one element not in S, hence at least one element not in [itex]V \cap S[/itex]. Thus [itex]dim(V) > dim(V \cap S)[/itex], and since dimensions are integers, this is the same as [itex]dim(V) \geq dim(V \cap S) + 1[/itex].

Similarly, S contains at least one element not in V, so [itex]dim(S) \geq dim(V \cap S) + 1[/itex].

Now apply those inequalities to

[tex]dim(V+S) = dim(V) + dim(S) - dim(V \cap S)[/tex]

to achieve a contradiction.
 
  • #7


gutnedawg said:
How do I come to the fact that

[tex] dim(V+S) = dim(V) + dim(S) - dim( V \cap S) [/tex]

This is a standard result that should be in just about any linear algebra textbook. E.g., theorem 2.18 in Sheldon Axler's "Linear Algebra Done Right." See page 33 in this online preview:

http://books.google.com/books?id=BN...esnum=1&ved=0CDoQ6AEwAA#v=onepage&q=&f=false"

Here is another proof (PDF file), but it looks more longwinded than it needs to be:

http://www.its.caltech.edu/~clyons/ma1b/intsumdimthm.pdf

[Edit]: See also Problem 16, parts 2 and 3 here:

http://en.wikibooks.org/wiki/Linear_Algebra/Combining_Subspaces
 
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FAQ: How to prove that the dim of two subspaces added together equals dim

How do I prove that the dimension of two subspaces added together equals the dimension of the sum?

To prove this, you can use the concept of linear independence. If you have two subspaces, A and B, their dimensions are given by the number of linearly independent vectors in each subspace. When you add these two subspaces together, you are essentially creating a new subspace that contains all the vectors from A and B. By definition, the dimension of a subspace is equal to the number of linearly independent vectors it contains. Therefore, if A and B are both linearly independent, their sum will also be linearly independent and thus have the same dimension.

Can I use a specific example to prove that the dimension of two subspaces added together equals the dimension of the sum?

Yes, you can use a specific example to illustrate this concept. For instance, let's say you have two subspaces, A and B, with dimensions 3 and 2 respectively. This means that A contains 3 linearly independent vectors and B contains 2 linearly independent vectors. When you add A and B together, you are essentially creating a new subspace with 5 linearly independent vectors, which is the sum of the dimensions of A and B.

Is it possible for the dimension of the sum of two subspaces to be less than the sum of their dimensions?

No, it is not possible for the dimension of the sum of two subspaces to be less than the sum of their dimensions. This is because the sum of two subspaces will always contain at least the same number of linearly independent vectors as the sum of their dimensions. In some cases, the sum of the dimensions may be equal to the dimension of the sum, but it can never be less.

Can I use the concept of bases to prove that the dimension of two subspaces added together equals the dimension of the sum?

Yes, you can use the concept of bases to prove this. Bases are sets of linearly independent vectors that span a subspace. When you add two subspaces together, their bases will also be added together to create a basis for the sum of the subspaces. Since the number of vectors in a basis is equal to the dimension of the subspace, the sum of the dimensions of the subspaces will also equal the dimension of the sum.

Are there any other methods I can use to prove that the dimension of two subspaces added together equals the dimension of the sum?

Yes, there are other methods you can use to prove this concept. One method is to use the concept of linear transformations. You can show that if you have two subspaces, A and B, and you add them together, their sum will be the range of a linear transformation. Since the dimension of the range is equal to the dimension of the subspace, this proves that the dimension of the sum is equal to the dimension of the subspaces added together. Another method is to use the concept of spanning sets and show that the sum of the spanning sets for A and B will also span the sum of the subspaces. This will prove that the dimension of the sum is equal to the sum of the dimensions of the subspaces.

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