How Do Ranks of Composite Linear Transformations Compare?

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The discussion focuses on proving properties of the ranks of composite linear transformations S and T, where S maps U to V and T maps V to W. Key points include that the rank of the composite transformation TS is less than or equal to the ranks of both T and S, with specific conditions for equality when S or T is nonsingular. Participants clarify the implications of nonsingularity, noting that it relates to the injectivity and surjectivity of the transformations, which can help establish the equalities in ranks. There is some confusion about the dimensions of the vector spaces involved, emphasizing that they can be over the same field without having the same number of entries. Overall, the discussion aims to solidify understanding of rank relationships in linear mappings.
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Homework Statement


Let S(U)=V and T(V)=W be linear maps where U,V, W are vector spaces over the same field K. Prove :

Homework Equations


a) Rank (TS) <= Rank (T)
b) Rank (TS) <= Rank (S)
c) if U=V and S is nonsingular then Rank (TS) = Rank (T)
d) if V=W and T is nonsingular then Rank (TS) = Rank (S)

The Attempt at a Solution


a) TS maps to W, so is T
b) TS maps to W, but S to V, but how do I show the ranks for (a) and (b)?
c) d) So inverse of S and T exists, and err...

U,V,W are vector space over the SAME field, does that mean they have the same number of entries, say R2, R3, etc etc
 
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mathmathmad said:

Homework Statement


Let S(U)=V and T(V)=W be linear maps where U,V, W are vector spaces over the same field K. Prove :

Homework Equations


a) Rank (TS) <= Rank (T)[/math]
The rank of a linear map is the dimension of its image space. Let w be in TS(U). Then there exist u in U such that TS(u)= w. Let v= S(u). Then T(v)= TS(u)= w. That is, if w is in TS(U) then it is in T(V). TS(U) is a subset of T(U) and, since they are both subspaces of W, TS(U) is a subspace of T(U).

b) Rank (TS) <= Rank (S)
Let \{u_1, u_2,\cdot\cdot\cdot, u_n\} be a basis for U. Then \{S(u_1), S(u_2), \cdot\cdot\cdot, S(u_n)\} spans S(U) (but is not neccessarily independent) so the dimension of S(U) is less than or equal to the dimension of U. Further \{TS(u_1), TS(u_2), \cdot\cdot\cdot, TS(u_n)\} spans TS(U) but is not necessarily independent so dimension of TS(U) is less than or equal to the dimension of S(U).

c) if U=V and S is nonsingular then Rank (TS) = Rank (T)
d) if V=W and T is nonsingular then Rank (TS) = Rank (S)

The Attempt at a Solution


a) TS maps to W, so is T
I have no idea what you mean by this. What "is T"? Are you saying TS= T? That's obviously not true.

b) TS maps to W, but S to V, but how do I show the ranks for (a) and (b)?
c) d) So inverse of S and T exists, and err...

U,V,W are vector space over the SAME field, does that mean they have the same number of entries, say R2, R3, etc etc
I have no idea what you mean by "entries". If you mean dimension, no. R2, R3, etc. are all "over the SAME field", the real numbers, but do NOT have the same "number of entries".
 
"TS maps to W, so is T"

sorry, what I meant was T also maps to W

for (c) and (d)
what does the the nonsingularity of the matrix imply?
how does that show that the ranks are both equal?
 
mathmathmad said:
"TS maps to W, so is T"

sorry, what I meant was T also maps to W

for (c) and (d)
what does the the nonsingularity of the matrix imply?
how does that show that the ranks are both equal?

I think the best way to show that the ranks are equal is by considering the surjectivity and injectivity of S and T respectively (since S and T are non-singular). From there, it should be pretty much straightforward.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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