How Do You Prove the Dimension of a Direct Sum Equals the Sum of Dimensions?

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SUMMARY

The dimension of the direct sum of subspaces \( U \) and \( W \) of a vector space \( V \) is equal to the sum of the dimensions of the individual subspaces if and only if their intersection is the zero vector, \( U \cap W = \{0\} \). To prove this, one must show that a combined basis from both subspaces spans \( V \) and is linearly independent. If a vector from the combined basis is dependent on others, it must belong to the span of the previous vectors, leading to a contradiction if the intersection condition holds.

PREREQUISITES
  • Understanding of vector spaces and subspaces
  • Familiarity with linear independence and dependence
  • Knowledge of basis and dimension concepts in linear algebra
  • Ability to work with intersection of subspaces
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  • Study the concept of direct sums in linear algebra
  • Learn about the properties of vector space intersections
  • Explore proofs related to linear independence and basis construction
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Students and educators in linear algebra, mathematicians interested in vector space theory, and anyone seeking to understand the properties of direct sums and their dimensions.

jecharla
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Exercise #17 in Linear Algebra done right is to prove that the dimension of the direct sum of subspaces of V is equal to the sum of the dimensions of the individual subspaces. I have been trying to figure this out for a few days now and I'm really stuck. Here's what I have got so far:

Choose a base of each of the subspaces and combine them in one list which clearly spans V and has the length we are looking for. Now we just have to show that this list is linearly independent.

If this list is not linearly independent than one of the vectors is in the span of the previous vectors. If I could show that this vector must be in the span of one of the other bases, then that would prove the result but I can't quite figure out how to get there. Any help would be greatly appreciated.
 
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jecharla said:
Exercise #17 in Linear Algebra done right is to prove that the dimension of the direct sum of subspaces of V is equal to the sum of the dimensions of the individual subspaces. I have been trying to figure this out for a few days now and I'm really stuck. Here's what I have got so far:

Choose a base of each of the subspaces and combine them in one list which clearly spans V and has the length we are looking for. Now we just have to show that this list is linearly independent.

If this list is not linearly independent than one of the vectors is in the span of the previous vectors. If I could show that this vector must be in the span of one of the other bases, then that would prove the result but I can't quite figure out how to get there. Any help would be greatly appreciated.



Let's do it for two subspaces as this summarizes the logical argument: suppose A:=\{v_1,...,v_k\}\,\,,\,\,B:=\{w_1,...,w_r\}\, are basis resp. of subspaces \,U,W\leq V\,\,,\,\,with\,\,\,U\cap W=\{0\}.

Suppose one of the vectors in \,\{v_1,...,v_k,w_1,...,w_r\}\, depends linearly on the preceeding ones. Then this must be

one of the \,w_i\,'s (why?) , so \,w_i\in Span\{v_1,...,v_k,w_1,...,w_{i-1}\}\,\Longrightarrow w_i=a_1v_1+...+a_kv_k+b_1w_1+...+b_{i-1}w_{i-1} We then get a_1v_1+...+a_kv_k=-b_1w_1-...-b_{i-1}w_{i-1}+w_i\in V\cap W=\{0\}

From here, \,a_1v_1+...+a_kv_k=0=-b_1w_1-...-b_{i-1}w_{i-1}+w_i\, , from where we reach at once our contradiction.

DonAntonio
 
jecharla said:
Exercise #17 in Linear Algebra done right is to prove that the dimension of the direct sum of subspaces of V is equal to the sum of the dimensions of the individual subspaces.
As stated, you can't prove this, it isn't true. It is true and you can prove it if you add the condition that the only vector contained in both subspaces is the 0 vector. Of course, your proof will have to use that condition.

I have been trying to figure this out for a few days now and I'm really stuck. Here's what I have got so far:

Choose a base of each of the subspaces and combine them in one list which clearly spans V and has the length we are looking for. Now we just have to show that this list is linearly independent.

If this list is not linearly independent than one of the vectors is in the span of the previous vectors. If I could show that this vector must be in the span of one of the other bases, then that would prove the result but I can't quite figure out how to get there. Any help would be greatly appreciated.
If they were not you could construct a non-zero vector that is in both subspaces.
 
HallsofIvy said:
As stated, you can't prove this, it isn't true. It is true and you can prove it if you add the condition that the only vector contained in both subspaces is the 0 vector. Of course, your proof will have to use that condition.



This condition is implicit in the direct sum thing: cero must be the intersection of any space and the sum of all the others, otherwise the sum is not direct.

Donantonio

If they were not you could construct a non-zero vector that is in both subspaces.
 
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