Dimension of preimage question

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The discussion centers on the properties of the inverse function \( g \) of a function \( f \) and its relationship with subspaces in linear algebra. It establishes that if \( U \) is a subspace of \( W \), then \( g(U) \) is also a subspace of \( V \). Furthermore, it proves the dimension formula \( \dim(g(U)) = \dim(U \cap \operatorname{Im}(f)) + \dim(\operatorname{ker}(f)) \) using linearity and the rank-nullity theorem. The proof relies on the assumption that \( f \) is linear and explores the implications of the kernel and image of \( f \).

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let g be the inverse function of f (not necessarily a bijective inverse function)
If S is any subset of W then the pre-image of S is

g(S) = {v ε V: f(v) ε S}

Suppose that U is a subspace of W.
Prove that g(U) is a subspace of V.
Also prove that
dim( g(U) )= dim( U intersect Im(f) ) + dim( ker (f) )

For the first part,
by linearity, f(av1+v2)=af(v1)+f(v2)=au1+ u2 ε U where v1ε g(U), v2ε g(U)
so av1+v2 ε g(U)---> a g(u1)+g(u2)ε g(U)
if f(v)=v.then g(U) is not empty
therefore, g(U) is a subspace.

For the second part,
I am not sure. can i just simply assume that U=W? then g(U) = V and U intersect im(f) is im(f) so clearly dim(V)=dim imf + dim kerf

Could anyone verify my first proof and give me a hint for the second part? Thanks in advance.
 
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Consider the restriction of ##f## on ##g(U)##. Then ##\operatorname{ker}f|_{g(U)}= \operatorname{ker}f## and the rank-nullity-theorem gives $$
\dim(U \cap \operatorname{im}f) = \dim \operatorname{im}f|_{g(U)} = \dim g(U) - \dim \operatorname{ker}f|_{g(U)}=\dim g(U) - \dim \operatorname{ker}f
$$
 

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