Nullspaces relation between components and overall matrix

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The discussion centers on the relationship between the nullspace of a combined matrix C, formed by stacking matrices A and B, and the individual nullspaces N(A) and N(B). It is clarified that N(C) is the intersection of N(A) and N(B), not their sum, because for Cx to equal zero, both Ax and Bx must be zero simultaneously. Examples are provided to illustrate this concept, showing that the nullspaces can be visualized as vectors that intersect at the origin. The participants also explore the geometric interpretation of nullspaces and their orthogonality. Ultimately, the key takeaway is that the nullspace of the combined matrix C reflects the common solutions of the equations defined by A and B.
worryingchem
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Homework Statement


If matrix ## C = \left[ {\begin{array}{c} A \\ B \ \end{array} } \right]## then how is N(C), the nullspace of C, related to N(A) and N(B)?

Homework Equations


Ax = 0; x = N(A)

The Attempt at a Solution


First, I thought that the relation between A and B with C is ## C = A + B ## so then I thought that ## N(C) = N(A) + N(B) ##.
But when I checked the solution it said N(C) = N(A) ∩ N(B)
and the only explanation is that ## Cx = \left[ {\begin{array}{c} Ax \\ Bx \ \end{array} } \right] = 0. ##
Can someone explain the solution to me?
 
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worryingchem said:

Homework Statement


If matrix ## C = \left[ {\begin{array}{c} A \\ B \ \end{array} } \right]## then how is N(C), the nullspace of C, related to N(A) and N(B)?

Homework Equations


Ax = 0; x = N(A)

The Attempt at a Solution


First, I thought that the relation between A and B with C is ## C = A + B ## so then I thought that ## N(C) = N(A) + N(B) ##.
But when I checked the solution it said N(C) = N(A) ∩ N(B)
and the only explanation is that ## Cx = \left[ {\begin{array}{c} Ax \\ Bx \ \end{array} } \right] = 0. ##
Can someone explain the solution to me?

I'm not sure why you aren't getting the explanation. If ##\left[ \begin{array}{c} Ax \\ Bx \ \end{array} \right]## is the zero vector doesn't that mean that BOTH ##Ax## and ##Bx## must be zero vectors? Not just one or the other? ##C## isn't equal to ##A+B##, it's equal to ##\left[ \begin{array}{c} A\\ 0 \ \end{array} \right]+\left[ \begin{array}{c} 0 \\ B \ \end{array} \right]##. Even if it were the null space of ##A+B## is not equal to the null space of ##A## plus the null space of ##B##.
 
Last edited:
I didn't understand how they went from ## Cx = \left[ {\begin{array}{c} Ax \\ Bx \ \end{array} } \right] = 0 ## to how N(C) is the intersection of N(A) and N(B). I just saw that the nullspaces were zero, but doesn't all nullspaces contain zero.

After some more thought, I did manage to visualize it if I use row vectors for ## A = \left[ {\begin{array}{cc} 1 & 1 \ \end{array} } \right] ## and ## B = \left[ {\begin{array}{cc} 1 & 2 \ \end{array} } \right] ##.
Then ## N(A) = \left[ {\begin{array}{c} 1 \\ -1 \ \end{array} } \right] ## and ## N(B) = \left[ {\begin{array}{c} 2 \\ -1 \ \end{array} } \right] ##. If I think of the nullspace as column vectors, then it's easier to visualize the nullspaces, and that they are perpendicular to the original matrix and intersect at 0.
When I make C, it would be ## \left[ {\begin{array}{cc} 1 & 1 \\ 1 & 2 \ \end{array} } \right] ## and ## N(C) = \left[ {\begin{array}{c} 0 & 0 \\ 0 & 0 \ \end{array} } \right] ##, the intersection of N(A) and N(B). Is this example right?

When I try to picture a plane though, I don't know how to define a plane in matrix notation and would the nullspace be a second plane with a normal vector orthogonal to the first plane's normal vector?
 
worryingchem said:
I didn't understand how they went from ## Cx = \left[ {\begin{array}{c} Ax \\ Bx \ \end{array} } \right] = 0 ## to how N(C) is the intersection of N(A) and N(B). I just saw that the nullspaces were zero, but doesn't all nullspaces contain zero.

After some more thought, I did manage to visualize it if I use row vectors for ## A = \left[ {\begin{array}{cc} 1 & 1 \ \end{array} } \right] ## and ## B = \left[ {\begin{array}{cc} 1 & 2 \ \end{array} } \right] ##.
Then ## N(A) = \left[ {\begin{array}{c} 1 \\ -1 \ \end{array} } \right] ## and ## N(B) = \left[ {\begin{array}{c} 2 \\ -1 \ \end{array} } \right] ##. If I think of the nullspace as column vectors, then it's easier to visualize the nullspaces, and that they are perpendicular to the original matrix and intersect at 0.
When I make C, it would be ## \left[ {\begin{array}{cc} 1 & 1 \\ 1 & 2 \ \end{array} } \right] ## and ## N(C) = \left[ {\begin{array}{c} 0 & 0 \\ 0 & 0 \ \end{array} } \right] ##, the intersection of N(A) and N(B). Is this example right?

When I try to picture a plane though, I don't know how to define a plane in matrix notation and would the nullspace be a second plane with a normal vector orthogonal to the first plane's normal vector?

You don't have to visualize it that precisely. If ##x## is the nullspace of ##C##, then ##Cx=\left[ {\begin{array}{cc} Ax \\ Bx \ \end{array} } \right]=\left[ {\begin{array}{cc} 0 \\ 0 \ \end{array} } \right]##, right? Doesn't that mean ##Ax=0## and ##Bx=0##? And doesn't that mean the ##x## is in the nullspace of both ##A## and ##B##?
 
Ah, I see.
Then, ## C*N(A) = \left[ {\begin{array}{c} A*N(A)\\ B*N(A) \ \end{array} } \right]=\left[ {\begin{array}{c} 0 \\ n \ \end{array} } \right] ##.
And ## C*N(B) = \left[ {\begin{array}{c} A*N(B)\\ B*N(B) \ \end{array} } \right]=\left[ {\begin{array}{c} n \\ 0 \ \end{array} } \right] ##.
n can be some non-zero numbers.
So in order to make ##\left[ {\begin{array}{c} 0 \\ 0 \ \end{array} } \right] ##, C has to be multiply by something that exists in both N(A) and N(B), the intersection point of the two, and that is x.
 
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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