Form of symmetric matrix of rank one

In summary, we proved that if $C$ is a symmetric matrix of rank 1, then it must have the form $C = aww^T$, where $a$ is a scalar and $w$ is a vector of norm one.
  • #1
i_a_n
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0
The question is:Let $C$ be a symmetric matrix of rank one. Prove that $C$ must have the form $C=aww^T$, where $a$ is a scalar and $w$ is a vector of norm one.(I think we can easily prove that if $C$ has the form $C=aww^T$, then $C$ is symmetric and of rank one. But what about the opposite direction...that is what we need to prove. How to prove this?)
 
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  • #2
ianchenmu said:
The question is:Let $C$ be a symmetric matrix of rank one. Prove that $C$ must have the form $C=aww^T$, where $a$ is a scalar and $w$ is a vector of norm one.(I think we can easily prove that if $C$ has the form $C=aww^T$, then $C$ is symmetric and of rank one. But what about the opposite direction...that is what we need to prove. How to prove this?)
If $C$ has rank 1 then the range space of $C$ is 1-dimensional. Let $w$ be a unit (column) vector in this subspace, then $Cw$ must be a scalar multiple of $w$, say $Cw = aw$. Since $C$ is symmetric, $w^TC = (Cw)^T = aw^T.$ Notice also that $w^Tw = 1$ since $w$ is a unit vector.

For any other column vector $x$, $Cx$ must also be a scalar multiple of $w$, say $Cx = \lambda_xw$, which we could equally well write $Cx = w\lambda_x$ since $\lambda$ is a scalar. Then $$\lambda_x = \lambda_x w^Tw = w^T(\lambda_xw) = w^T(Cx) = (w^TC)x = aw^Tx,$$ hence $Cx = w\lambda_x = w(aw^Tx) = aww^Tx$. That holds for all vectors $x$, therefore $C = aww^T.$
 

Related to Form of symmetric matrix of rank one

1. What is a symmetric matrix of rank one?

A symmetric matrix of rank one is a square matrix where all elements outside of the main diagonal are equal to zero, and the elements on the main diagonal are equal to a single non-zero value. This type of matrix can also be represented as the outer product of a column vector with itself.

2. How can I identify a symmetric matrix of rank one?

A symmetric matrix of rank one can be identified by checking if all elements outside of the main diagonal are equal to zero, and if the elements on the main diagonal are equal to a single non-zero value. Additionally, the matrix must be a square matrix.

3. What is the significance of a symmetric matrix of rank one?

A symmetric matrix of rank one has several applications in linear algebra and optimization. It can be used to represent quadratic forms, and it has special properties that make it useful in solving optimization problems.

4. How is a symmetric matrix of rank one different from a general symmetric matrix?

A general symmetric matrix can have non-zero elements outside of the main diagonal, while a symmetric matrix of rank one only has a single non-zero value on the main diagonal. Additionally, the rank of a general symmetric matrix can be greater than one, while the rank of a symmetric matrix of rank one is always equal to one.

5. Can a symmetric matrix of rank one be diagonalized?

Yes, a symmetric matrix of rank one can be diagonalized by finding its eigenvalues and eigenvectors. Since the matrix has rank one, it will have a single non-zero eigenvalue, and its corresponding eigenvector will be the column vector used to form the matrix. This means that the matrix can be written as a diagonal matrix with the eigenvalue on the main diagonal and a column vector on the side.

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