LINEAR ALGEBRA: Consider 2X2 Matrices - What are the subspaces?

In summary, subspaces in linear algebra are subsets of vector spaces that satisfy the properties of a vector space. They are important in understanding the structure and behavior of vector spaces and allow for more efficient operations on vectors and matrices. In relation to 2x2 matrices, subspaces include the column space, row space, null space, and the entire vector space. The column space represents all possible linear combinations of the columns, while the row space represents all possible linear combinations of the rows. To determine the subspaces of a 2x2 matrix, one can find its column space, row space, and null space by reducing the matrix to its echelon form and solving the system of equations represented by the matrix.
  • #1
VinnyCee
489
0
Consider 2-by-2 matrices [itex]\mathbf{A} =\left( \begin{array}{cc}a & b \\c & d \\\end{array} \right) \in \mathbbm{R}^{2 X 2}[/itex]. Which of the following are subspaces of [itex]\mathbbm{R}^{2 X 2}[/itex]?

(A) {A | c = 0}

(B) {A | a + d = 0}

(C) {A | ad - bc = 0}

(D) {A | b = c}

(E) {A | Av = 2v}, where v is some vector in [itex]R^2[/itex].






I think that all except the last would be subspaces of the 2 X 2 set of matrices. I know that choice (C) is the determinent of the matrix, which is in the subspace of it's own matrix, right?

Also, how would I make a case for the first four choices using the 3 "rules" that determine if a vector is a subspace of another?

(1) {0} must be in the subset for it to be a subset.

(2) if v is in W then a * v is in W for all real numbers a.

(3) if u and v are in W, then u + v is in W.
 
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  • #2
For (C), you should be able to come up with 2 matrices with zero determinant that add to a matrix with non-zero determinant.

The set (E) obviously violates one of the rules.
 
  • #3
(C) {A | ad - bc = 0}

Let
[tex]\mathbf{U} =\left( \begin{array}{cc}a & b \\c & d \\\end{array} \right) \in S[/tex] and
[tex]\mathbf{V} =\left( \begin{array}{cc}e & f \\g & h \\\end{array} \right) \in S[/tex], where S is the subspace of [tex]\mathbbm{R}^{2 X 2}[/tex] described with (C).
Then, U + V = W has to be in S.
[tex]\mathbf{W} =\left( \begin{array}{cc}a+e & b+f \\c+g & d+h \\\end{array} \right) \in S[/tex]. Further on, [tex](a+e)(d+h)-(c+g)(b+f)=0[/tex] implies [tex]\frac{ah+ed}{bg-fc}=1[/tex], from which we obtain [tex]bg \neq fc[/tex] (1). So, we have shown that W is in the same subspace as U and V just for the matrices U and V such that (1) is true. But, it should be true for every two matrices U and V satisfying only the property stated in (C). Hence, (C) is no subspace.
 
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  • #4
So, in order to do this "proving" stuff. A person should assign variables (presumably the set of all real numbers) to two of the types of spaces (or matrix m X n, etc.) being questioned as subspaces? Then apply the three rules to see if they are broken?

How, exactly, do we know that the U and V matrices above do not satisfy rule number 3(if u and v are in W, then u + v is in W)?
 
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  • #5
Radou did a proof by contradiction. Assume what you want to prove and show that it leads to a contradiction.

The one I suggested would be a proof by counterexample.
 
  • #6
Only (A), (B) and (D) are subspaces?
 
  • #7
Yeah, you need to show that. Radou basically gave you the template for rule 3: show that for arbitrary U and V in the subset, W = U + V is also in the subset.
 
  • #8
For example, I can use rule 3 for case (A) like so?:

[tex]\mathbf{U} =\left( \begin{array}{cc}a & b \\0 & d \\\end{array} \right) \in S[/tex]

[tex]\mathbf{V} =\left( \begin{array}{cc}e & f \\0 & h \\\end{array} \right) \in S[/tex]

[tex]\mathbf{W} =\left( \begin{array}{cc}a+e & b+f \\0+0 & d+h \\\end{array} \right) \in S[/tex]


Does this prove (for rule 3 only) that case (A) is a subspace of [itex]R^{2 X 2}[/itex]?

EDIT:

For rule 2 -

[tex]a\,\left( \begin{array}{cc}a & b \\0 & d \\\end{array} \right) \in S[/tex], where the first a is a real number.

is true?
 
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  • #9
"If v [itex]\in[/itex] W then av [itex]\in[/itex] W for all a [itex]\in[/itex] R."

This is rule 2, how would I go about defineing a vector v that is in W?

[tex]\overrightarrow{v}\,=\,v_1,\,v_2,\,...,\,v_n[/tex]?
 
  • #10
VinnyCee said:
For example, I can use rule 3 for case (A) like so?:

[tex]\mathbf{U} =\left( \begin{array}{cc}a & b \\0 & d \\\end{array} \right) \in S[/tex]

[tex]\mathbf{V} =\left( \begin{array}{cc}e & f \\0 & h \\\end{array} \right) \in S[/tex]

[tex]\mathbf{W} =\left( \begin{array}{cc}a+e & b+f \\0+0 & d+h \\\end{array} \right) \in S[/tex]Does this prove (for rule 3 only) that case (A) is a subspace of [itex]R^{2 X 2}[/itex]?

Well, simplify everything that can be simplified, and it should be obvious that you have a new element that's a member of the subset.

EDIT:

For rule 2 -

[tex]a\,\left( \begin{array}{cc}a & b \\0 & d \\\end{array} \right) \in S[/tex], where the first a is a real number.

is true?

Well, choose a variable name that's not going to confuse the real number multiplier with one of the matrix elements.

Then...do the matrix arithmetic. That's basically all you do to check rules (2) & (3): do the matrix arithmetic for the particular subspace rule, simplify whatever can be simplified, then check to see if the resulting matrix is a member of the subset according to the definition (which, if it's not obvious by inspection, is just more matrix arithmetic). For rule (1), you just need to check that the 0 matrix is a legal member of the subset.
 
  • #11
VinnyCee said:
"If v [itex]\in[/itex] W then av [itex]\in[/itex] W for all a [itex]\in[/itex] R."

This is rule 2, how would I go about defineing a vector v that is in W?

[tex]\overrightarrow{v}\,=\,v_1,\,v_2,\,...,\,v_n[/tex]?

The vectors in this space are 2x2 matrices, so just construct an arbitrary 2x2 matrix like V above.
 

1. What are subspaces in linear algebra?

Subspaces in linear algebra refer to a subset of a vector space that satisfies the properties of a vector space. This means that it is closed under vector addition and scalar multiplication.

2. What is the importance of subspaces in linear algebra?

Subspaces are important in linear algebra because they help us understand the structure and behavior of vector spaces. They also allow us to perform operations on vectors and matrices more efficiently.

3. How are subspaces related to 2x2 matrices?

2x2 matrices can represent linear transformations in two-dimensional vector spaces. The subspaces of a 2x2 matrix are the column space, row space, null space, and the entire vector space.

4. What is the difference between a column space and a row space?

The column space of a matrix is the span of its column vectors, while the row space is the span of its row vectors. In other words, the column space consists of all possible linear combinations of the columns, while the row space consists of all possible linear combinations of the rows.

5. How can we determine the subspaces of a 2x2 matrix?

The subspaces of a 2x2 matrix can be determined by finding its column space and row space, as well as its null space. The column space and row space can be found by reducing the matrix to its echelon form, while the null space can be found by solving the system of equations represented by the matrix.

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