Range space of linear mappings

Jennifer1990
Messages
55
Reaction score
0

Homework Statement


Let L : Rn --> Rm and M : Rm --> Rp be linear mappings.
a)Prove that rank( M o L) <= rank(L).
b)Give an example such that the rank(M o L) < rank(M) and rank(L)

Homework Equations


None


The Attempt at a Solution


a)I see that (M o L) takes all vectors in Rn and maps them to vectors in Rm then maps these vectors to vectors in Rp. (L) also takes all vectors in Rn and maps them to Rm. From this, i get the impression that rank(M o L) = rank (L) because the quantity of vectors should not change when (M o L) maps vectors in Rm to Rp.

b)Is there a method to get such a matrix or do I have to use trial and error?
 
Physics news on Phys.org
Hints:

For part a:
Note that the range of M is a subspace of Rp with dimension Rank(M).
Likewise, the range of L is a subspace of Rm with dimension Rank(L).
For the composition ML, notice that after L is applied, the range of L is not necessarily all of Rm. Moreover, when you next apply M, it is only acting on that subspace, range of L.

For part b, try matrices from R^2 to R^2. Make both of them with rank 1, yet the composition has rank 0.
 
Thread 'Use greedy vertex coloring algorithm to prove the upper bound of χ'
Hi! I am struggling with the exercise I mentioned under "Homework statement". The exercise is about a specific "greedy vertex coloring algorithm". One definition (which matches what my book uses) can be found here: https://people.cs.uchicago.edu/~laci/HANDOUTS/greedycoloring.pdf Here is also a screenshot of the relevant parts of the linked PDF, i.e. the def. of the algorithm: Sadly I don't have much to show as far as a solution attempt goes, as I am stuck on how to proceed. I thought...
Back
Top