Linear Algebra Symmetric Matrix Set Question

In summary, the conversation discusses the size or dimension of a set of symmetric matrices, where the number of free variables or vectors in a basis set is used to determine the dimension. It is also mentioned that for nxn matrices, the number of vectors in a basis set is equivalent to the size of the matrix squared. The conversation also touches on the idea of dividing matrix entries into diagonal and off-diagonal elements to determine the dimension.
  • #1
Gamble93
6
0
First of all, I apologize if this is in the wrong place. I didn't really know where it should be placed and if it is in the wrong place I am sorry.

This question was on my recent Linear Algebra I final exam and I had no idea how to do it when I was writing the exam and I'm still stumped by it. I'm simply curious as how to go about obtaining the solution mostly because it has been bugging me for a few weeks now. Also, this is the first time using LaTeX typesetting so forgive me if it's sloppy.

Let [itex]A[/itex] be any [itex] n \mbox{ by } n [/itex] matrix.

Let [itex]S[/itex] be defined as:

[tex] \displaystyle{S=\{A|A=A^T\}} [/tex]
What is the size of [itex]S[/itex] ?

Thanks in advance for any help.
 
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  • #2
I suppose you're asking for the dimension of the basis set when you say "size"? I'll assume so. The way to approach this problem is to determine if your set of all symmetric matrices forms a subspace of R^n and then find a suitable basis. The dimension will be the number of elements in your basis set. This is what I think you're asking, but I find your question vague. Do you know how to do this?
 
  • #3
In addition to division's answer: the dimension of a space can often be seen as the number of free variables. For example, a 2x2-matrix

[tex]\left(\begin{array}{cc} a & b\\ c & d \end{array}\right)[/tex]

has 4 free variables so has dimension 4 (this is NOT a rigorous argument, but merely an intuition). However, if you want the matrix to be symmetric, then it must happen that b=c. So now there are only 3 free variables, so the dimension is 3.

The question now asks you to calculate this for nxn matrices.
 
  • #4
Thank you both for your answers. The question I posted was word for word what was on my exam. I also assumed that it was the dimension of the set he was asking for. When I get an opportunity I'll see if I can figure out the answer. Thanks again both of you.
 
  • #5
micromass said:
In addition to division's answer: the dimension of a space can often be seen as the number of free variables. For example, a 2x2-matrix

[tex]\left(\begin{array}{cc} a & b\\ c & d \end{array}\right)[/tex]

has 4 free variables so has dimension 4 (this is NOT a rigorous argument, but merely an intuition). However, if you want the matrix to be symmetric, then it must happen that b=c. So now there are only 3 free variables, so the dimension is 3.

The question now asks you to calculate this for nxn matrices.

Hello, i find a paradox here. We know that dimension implies the number of vectors in a basis set needed to traverse the whole space. And the basis theorem states that a matrix of size nxn ( be it symmetric or not ) , needs only n vectors in it's basis set to traverse the space ?

Then, where could i be going wrong ?
 
  • #6
one basis for the set of all 2x2 matrices is:

[tex]\begin{bmatrix}1&0\\0&0 \end{bmatrix},\begin{bmatrix}0&1\\0&0 \end{bmatrix},\begin{bmatrix}0&0\\1&0 \end{bmatrix},\begin{bmatrix}0&0\\0&1 \end{bmatrix}[/tex]

however, since for a symmetric matrix the 2,1 entry must equal the 1,2 entry, we only need the following 3 matrices as a basis:

[tex]\begin{bmatrix}1&0\\0&0 \end{bmatrix}, \begin{bmatrix}0&1\\1&0 \end{bmatrix}, \begin{bmatrix}0&0\\0&1 \end{bmatrix}[/tex]

for the general nxn case, it helps to divide the matrix entries into 2 disjoint sets:

diagonal entries, off-diagonal entries

if a matrix is symmetric, it tells us something about the off-diagonal enties (which are of course, divided into two equal subsets: above diagonal, and below diagonal entires). can you think of what this might be?

vish_maths said:
Hello, i find a paradox here. We know that dimension implies the number of vectors in a basis set needed to traverse the whole space. And the basis theorem states that a matrix of size nxn ( be it symmetric or not ) , needs only n vectors in it's basis set to traverse the space ?

Then, where could i be going wrong ?

dim(Mat(n,F)) = n2, not n.
 
  • #7
Deveno said:
one basis for the set of all 2x2 matrices is:

[tex]\begin{bmatrix}1&0\\0&0 \end{bmatrix},\begin{bmatrix}0&1\\0&0 \end{bmatrix},\begin{bmatrix}0&0\\1&0 \end{bmatrix},\begin{bmatrix}0&0\\0&1 \end{bmatrix}[/tex]

however, since for a symmetric matrix the 2,1 entry must equal the 1,2 entry, we only need the following 3 matrices as a basis:

[tex]\begin{bmatrix}1&0\\0&0 \end{bmatrix}, \begin{bmatrix}0&1\\1&0 \end{bmatrix}, \begin{bmatrix}0&0\\0&1 \end{bmatrix}[/tex]

for the general nxn case, it helps to divide the matrix entries into 2 disjoint sets:

diagonal entries, off-diagonal entries

if a matrix is symmetric, it tells us something about the off-diagonal enties (which are of course, divided into two equal subsets: above diagonal, and below diagonal entires). can you think of what this might be?



dim(Mat(n,F)) = n2, not n.

Yep got it :) was confusing the column space :)
 

Related to Linear Algebra Symmetric Matrix Set Question

1. What is a symmetric matrix?

A symmetric matrix is a square matrix in which the elements above and below the main diagonal are equal. In other words, the element at row i and column j is equal to the element at row j and column i.

2. How can a symmetric matrix be represented?

A symmetric matrix can be represented in a variety of ways, such as using a system of linear equations, a matrix equation, or a vector equation. It can also be represented visually as a symmetric graph or a symmetric geometric figure.

3. What are the properties of a symmetric matrix?

A symmetric matrix has several key properties, including:

  • It is always square (same number of rows and columns).
  • It is equal to its transpose, meaning that the rows become columns and the columns become rows.
  • It has real eigenvalues (the solutions to the characteristic equation are real numbers).
  • It is always diagonalizable, meaning that it can be expressed as a product of diagonal and orthogonal matrices.

4. How is a symmetric matrix used in linear algebra?

Symmetric matrices have many applications in linear algebra, including:

  • They are used to represent and solve systems of linear equations.
  • They can be used in matrix operations such as addition, multiplication, and inversion.
  • They are used to solve optimization problems, such as finding the shortest distance between two points.
  • They are used in statistics and data analysis, such as in principal component analysis.

5. Can a non-square matrix be symmetric?

No, a non-square matrix cannot be symmetric. In order for a matrix to be symmetric, it must have the same number of rows and columns. Non-square matrices do not have this property and therefore cannot be symmetric.

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