Determinant of outer product matrices

In summary, the question asks to find the determinant of A + uv^T where u and v are n-dimensional vectors and A is a n x n matrix with a non-zero determinant. After trying different methods, it is found that the determinant of A + uv^T can be expressed as 1 + u^Tv. This is achieved by considering the eigenvalues of the special case A = I and using the fact that outer product matrices have rank 1. Other methods, such as using the equation A\vec{\eta} = \lambda\vec{\eta}, are also explored but do not lead to a solution. Finally, the equation \mathrm{det}\left(A + uv^T\right) = \mathrm{
  • #1
seanbow
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0

Homework Statement


Given [itex]u, v \in \mathbb{R}^{n}[/itex], and [itex]A \in \mathbb{R}^{n \times n}[/itex], [itex]\mathrm{det}\left(A\right) \neq 0[/itex], find [itex]\mathrm{det}\left( A + uv^{T} \right)[/itex]

Homework Equations


Generic determinant and eigenvalue equations, I suppose.

The Attempt at a Solution


Hoping to gain some insight, I found the determinant for the special case [itex] A = I [/itex]. In that case we can see that the eigenvalues of [itex]I + uv^T[/itex] satisfy
[tex] \mathrm{det}\left(I + uv^T + \lambda I\right) = \mathrm{det}\left( uv^T + \left( \lambda + 1\right) I\right) = 0 [/tex]
so we see that the eigenvalues of [itex] uv^T + I [/itex] are those of [itex] uv^T [/itex] plus one.

Outer product matrices have rank 1, so [itex] uv^T [/itex] has only one nonzero eigenvalue (which is pretty easy to see is equal to [itex] \mathrm{tr}\left( uv^T \right) = u^{T}v[/itex]).

The determinant of [itex] uv^T + I [/itex] is equal to the product of its eigenvalues. Since it only has one eigenvalue not equal to 1, the determinant will equal that eigenvalue, or [itex] \mathrm{tr}\left(uv^T\right) + 1 = 1 + u^Tv [/itex]

I tried similar methods replacing [itex]I[/itex] with the more generic [itex]A[/itex] without any luck. I also tried starting from the equation
[tex] A\vec{\eta} = \lambda\vec{\eta} [/tex]
again without any luck.

I got to the equation
[tex] \mathrm{det}\left(A + uv^T\right) = \mathrm{det}(A) \mathrm{det}\left( I + A^{-1} u v^T \right) [/tex]
but I don't think it's very useful.
 
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  • #2
I'm wondering if there's a smart way to get the answer without resorting to explicitly finding the eigenvalues of A + uv^T, which would be pretty tedious. Any advice would be appreciated.
 

Related to Determinant of outer product matrices

1. What is the determinant of an outer product matrix?

The determinant of an outer product matrix is equal to the product of the determinants of its two constituent vectors. It can also be thought of as the area of the parallelogram formed by the two vectors.

2. How is the determinant of an outer product matrix related to linear independence?

If the determinant of an outer product matrix is equal to zero, it means that the two constituent vectors are linearly dependent. This is because the determinant represents the volume of the parallelepiped formed by the vectors, and if the volume is zero, the vectors lie on the same plane and are therefore linearly dependent.

3. Can the determinant of an outer product matrix be negative?

Yes, the determinant of an outer product matrix can be negative. This occurs when the two constituent vectors form a clockwise rotation, resulting in a negative area for the parallelogram and a negative determinant value.

4. How is the determinant of an outer product matrix used in cross product calculations?

The determinant of an outer product matrix is used in the cross product formula to find the magnitude of the resulting vector. It is also used to determine the direction of the resulting vector by considering the right-hand rule.

5. Can the determinant of an outer product matrix be used to find the angle between two vectors?

No, the determinant of an outer product matrix cannot be used to directly find the angle between two vectors. However, it can be used in conjunction with the dot product to find the angle using the formula: cosθ = (u∙v)/(|u||v|) = det(u,v)/(|u||v|).

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