Intro to Linear Algebra - Nullspace of Rank 1 Matrix

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SUMMARY

The discussion clarifies that the nullspace of a rank 1 matrix in R^n is indeed an (n-1) dimensional subspace, often referred to as a hyperplane. For example, a 2x2 matrix with rank 1 has a nullspace that is a line in R^2, while a 3x4 matrix with rank 1 has a nullspace that is a hyperplane in R^4. The confusion arises from terminology, as the term "plane" is sometimes used informally to describe these subspaces, but it is more accurate to refer to them as hyperplanes in higher dimensions.

PREREQUISITES
  • Understanding of matrix rank and its implications
  • Familiarity with the concept of nullspace in linear algebra
  • Knowledge of vector spaces and subspaces
  • Basic proficiency in R^n notation and geometry
NEXT STEPS
  • Study the properties of nullspaces in linear algebra
  • Learn about the relationship between matrix rank and nullity
  • Explore the concept of hyperplanes in higher dimensions
  • Investigate the geometric interpretations of linear transformations
USEFUL FOR

Students of linear algebra, educators teaching matrix theory, and anyone interested in the geometric aspects of vector spaces and nullspaces.

fractalizard
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Homework Statement
Given A is a mxn matrix with rank 1, the nullspace is a _____ in R^n.
Relevant Equations
N(A) = Linear combination of "special solutions" to A
The published solutions indicate that the nullspace is a plane in R^n. Why isn't the nullspace an n-1 dimensional space within R^n? For example, if I understand things correctly, the 1x2 matrix [1 2] would have a nullspace represented by any linear combination of the vector (-2,1), which would be a line.
 
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An (n-1) dimensional subspace in \mathbb{R}^n is analagous to a plane in \mathbb{R}^3: they are given by an equation of the form \mathbf{x} \cdot \mathbf{n} = 0.
 
fractalizard said:
Homework Statement: Given A is a mxn matrix with rank 1, the nullspace is a _____ in R^n.
Relevant Equations: N(A) = Linear combination of "special solutions" to A

The published solutions indicate that the nullspace is a plane in R^n.
That sounds wrong. Are you sure that you copied the problem statement exactly? The problem statement or the book answer might have a typo. Or the book might just need some more proofreading. It's very hard to eliminate all errors from a book.
fractalizard said:
Why isn't the nullspace an n-1 dimensional space within R^n?
It is. You can verify the properties of a subspace.
 
fractalizard said:
Homework Statement: Given A is a mxn matrix with rank 1, the nullspace is a _____ in R^n.
Relevant Equations: N(A) = Linear combination of "special solutions" to A

The published solutions indicate that the nullspace is a plane in R^n. Why isn't the nullspace an n-1 dimensional space within R^n? For example, if I understand things correctly, the 1x2 matrix [1 2] would have a nullspace represented by any linear combination of the vector (-2,1), which would be a line.
Perhaps the authors of the solution meant that the nullspace was a hyperplane; an object of dimension one less than that of ##\mathbb R^n##.

For a 2x2 matrix of rank 1, the domain is ##\mathbb R^2## and the nullspace is of dimension 1, so the nullspace is a line in ##\mathbb R^2##.

For a 3x4 matrix of rank 1, the domain is ##\mathbb R^4## and the nullspace is of dimension 3, so the nullspace is a hyperplane in ##\mathbb R^4##.
 
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Wow, this place is great - thanks for the quick replies. I suspected that this might be an error in the solution. FYI, my posted problem statement was only the piece of the original problem that I was having trouble with, here is the full problem statement:

40 only.png
And from the solution manual:

40 answer.png


The highlighted line is the piece I am having trouble understanding, the rest of the solution makes sense to me.
 
fractalizard said:
The highlighted line is the piece I am having trouble understanding, the rest of the solution makes sense to me.

As I stated above, every (n - 1) dimensional subspace is \{ \mathbf{x} \in \mathbb{R}^n: \mathbf{x} \cdot \mathbf{a} = x_1a_1 + \cdots + x_na_n = 0\} for some \mathbf{a} \neq 0. This is analagous to a plane in \mathbb{R}^3. In higher dimensions one might more properly call it a hyperplane.
 
fractalizard said:
And from the solution manual:

View attachment 326075
The highlighted line is the piece I am having trouble understanding, the rest of the solution makes sense to me.
Hi @fractalizard. Welcome to PF.

In addition to the other excellent replies I’d like to add a (non-mathematician's) example which might help.

Say ##A## is a ##4 \times 4## matrix. If the rank = 1 then any row is a scalar multiple of any other row, For example:

##A = \begin {bmatrix}
a&b&c&d \\
3a&3b&3c&3d\\
-2a&-2b&-2c&-2d\\
4a&4b&4c&4d
\end{bmatrix}##

So in this example we have rows: ##R_2=3R_1, ~R_3= -2R_1## and ##R_4 =4R_1##.

Take the vector ##\textbf {x}=\begin {bmatrix} x_1\\x_2\\x_3\\x_4 \end {bmatrix}##

##A \textbf {x}=\begin {bmatrix}
R_1\cdot \textbf {x}\\
3R_1\cdot \textbf {x}\\
-2R_1\cdot \textbf {x}\\
4R_1\cdot \textbf {x}
\end {bmatrix}##

To make ##A \textbf {x}=0 ## (i.e. for ##\textbf {x}## to be in A’s null space) we require only that ##R_1\cdot \textbf {x} = 0##.

This gives the required ‘single equation’ (mentioned in the soution manual): ##ax_1 + bx_2 + cx_3 + dx_4= 0##

This equation defines a ‘plane’ in ##\mathbb R^n##. Though, as already has been said, for n>3 the term ‘hyperplane’ could be used to avoid confusion with 2D planes. (Also, note that for n = 2, the so-called ‘plane’ would a line!)
 
pasmith said:
As I stated above, every (n - 1) dimensional subspace is \{ \mathbf{x} \in \mathbb{R}^n: \mathbf{x} \cdot \mathbf{a} = x_1a_1 + \cdots + x_na_n = 0\} for some \mathbf{a} \neq 0. This is analagous to a plane in \mathbb{R}^3. In higher dimensions one might more properly call it a hyperplane.

The same way a line is always 1 dimension, I would think of a plane with no prefix as being 2 dimensions.
 
Office_Shredder said:
I would think of a plane with no prefix as being 2 dimensions.
This...
 

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