Can a Linear Transformation Be Onto If the Codomain's Dimension Is Higher?

AI Thread Summary
A linear transformation T from an n-dimensional space V to an m-dimensional space W cannot be onto if m is greater than n, as there will be elements in W that cannot be reached by any vector in V. This is due to the rank-nullity theorem, which indicates that the dimension of the range R(T) must be less than or equal to n. Conversely, if m is less than n, T cannot be one-to-one because there will be infinitely many solutions for some vectors in W. The discussion highlights the importance of understanding the relationship between the dimensions of the domain and codomain in linear transformations. The insights provided clarify the conditions under which a linear transformation can be onto or one-to-one.
discoverer02
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Linear Transformation -- Onto

I'm having trouble with the first part of the following problem:

Let T be a linear transformation from an n-dimensional space V into an m-dimensional space W.

a) If m>n, show that T cannot be a mapping from V onto W.

b) if m<n, show that T cannot be one-to-one.

Part b) I can see. I think. T(v) = Av = w The matrix A will have more columns than rows (more unknowns than equations), so there will be infinitely solutions (more than one mapping from a v in V to a w in W).

I'm stumped by part a). I'm not seeing how m>n guarantees that there are w 's in W that aren't part of R(T).

A nudge in the right direction would be greatly appreciated.

Thanks.
 
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Why doesn't the same approach work?
 
I'm wondering the same thing, so there must be something that I'm not seeing.

I'll think about it some more.

Thanks.
 
Well, for a linear map: T:V^n \rightarrow W^m where n&lt;m

There is a useful formula which describes subspaces of V and W in terms of conditions they satisfy with respect to T. Then have a look at the dimension of these subspaces, the dimension of V, and the dimension of W. You should be able to establish that there are certain elements in W that aren't the image of any element in V. Hint: Consider a basis of W.
 
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Hint: Do you think that T inverse is defined for all of W?
 
OK, let's see what I've got so far:

A basis of W would consist of 3 elements, A basis of V would consist of 2 elements.

T(x + y ) = T(x ) + T(y )
T(kx ) = kT(x )

I also have the equation dim(ker(T)) + dim(R(T)) = dim(R2) = 2

Anyway you look at it dim(R(T)) <= 2. This means that any other element in R(T) is a linear combination of these two elements. But W has a basis of 3 elements meaning that R(T) could not possibly contain at least one of W's basis elements.

I think this makes sense finally. I'll think about it some more just to make sure it's solid.

Thanks very much for the hints.

discoverer02
 
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