Proving the Formula for Determinants by Induction

In summary, the conversation is about proving a formula for the determinant of a given matrix using the Laplace theorem and induction. The formula is $\det (\lambda u_n-m_n) =\lambda^n+\sum_{i=0}^{n-1}a_i \lambda^i$. There is some confusion about the base case for the induction, as $m_n$ is not defined for $n=1$. It is suggested to take the base case as $n=2$.
  • #1
mathmari
Gold Member
MHB
5,049
7
Hey!

Let $\mathbb{K}$ be a field and let $1\leq n\in \mathbb{N}$. Let $a_0, \ldots , a_{n-1}\in \mathbb{K}$ and let $m_n\in M_n(\mathbb{K})$ be given by \begin{equation*}m_n:=\begin{pmatrix}0 & 0 & \ldots & 0 & -a_0 \\ 1 & \ddots & \ddots & \vdots & \vdots \\ 0 & \ddots & \ddots & 0 & \vdots \\ \vdots & \ddots & \ddots & 0 & \vdots \\ 0 & \ldots & 0 & 1 & -a_{n-1}\end{pmatrix}\end{equation*}

I want to show that for $\lambda\in \mathbb{K}$ it holds that $\displaystyle{\det (\lambda u_n-m_n) =\lambda^n+\sum_{i=0}^{n-1}a_i \lambda^i}$. First I applied the Laplace theorem to show that the formula bust be this one:
\begin{equation*}\det (\lambda u_n-m_n)=\begin{vmatrix}\lambda & 0 & \ldots & 0 & a_0 \\ -1 & \ddots & \ddots & \vdots & \vdots \\ 0 & \ddots & \ddots & 0 & \vdots \\ \vdots & \ddots & \ddots & \lambda & \vdots \\ 0 & \ldots & 0 & -1 & \lambda+a_{n-1}\end{vmatrix}\end{equation*}
Laplace as for the first row:
\begin{equation*}\det (\lambda u_n-m_n)=\begin{vmatrix}\lambda & 0 & \ldots & 0 & a_0 \\ -1 & \ddots & \ddots & \vdots & \vdots \\ 0 & \ddots & \ddots & 0 & \vdots \\ \vdots & \ddots & \ddots & \lambda & \vdots \\ 0 & \ldots & 0 & -1 & \lambda+a_{n-1}\end{vmatrix}=\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^{n+1}a_0\begin{vmatrix}-1 & \lambda & \ddots & \vdots \\ 0 & \ddots & \ddots & 0 \\ \vdots & \ddots & \ddots & \lambda \\ 0 & \ldots & 0 & -1 \end{vmatrix}\end{equation*}
The matrix $\begin{pmatrix}-1 & \lambda & \ddots & \vdots \\ 0 & \ddots & \ddots & 0 \\ \vdots & \ddots & \ddots & \lambda \\ 0 & \ldots & 0 & -1 \end{pmatrix}$ is a triangular matrix, so the determiannt is the product of the diagonal elements, i.e. $(-1)^{n-1}$.

So we get \begin{align*}\det (\lambda u_n-m_n)&=\begin{vmatrix}\lambda & 0 & \ldots & 0 & a_0 \\ -1 & \ddots & \ddots & \vdots & \vdots \\ 0 & \ddots & \ddots & 0 & \vdots \\ \vdots & \ddots & \ddots & \lambda & \vdots \\ 0 & \ldots & 0 & -1 & \lambda+a_{n-1}\end{vmatrix} =\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^{n+1}a_0(-1)^{n-1}\\ & =\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^{2n}a_0 =\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+a_0\end{align*}
We expand again as for the first row:
\begin{align*}\det (\lambda u_n-m_n)&=\lambda \left (\lambda \begin{vmatrix} \lambda & 0 & a_2 \\ \ddots & \lambda & \vdots \\ 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^na_1\begin{vmatrix} -1 & \ddots & 0 \\ \ddots & \ddots & \lambda \\ \ldots & 0 & -1 \end{vmatrix}\right )+a_0\\ & =\lambda \left (\lambda \begin{vmatrix} \lambda & 0 & a_2 \\ \ddots & \lambda & \vdots \\ 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^na_1(-1)^{n-2}\right )+a_0 \\ & =\lambda \left (\lambda \begin{vmatrix} \lambda & 0 & a_2 \\ \ddots & \lambda & \vdots \\ 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^{2n-2}a_1\right )+a_0 \\ & =\lambda^2 \begin{vmatrix} \lambda & 0 & a_2 \\ \ddots & \lambda & \vdots \\ 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+ a_1 \lambda+a_0\end{align*}
We expand again as for the first row:
\begin{align*}\det (\lambda u_n-m_n)&=\lambda^2 \left (\lambda \begin{vmatrix} \lambda & 0 & a_3 \\ \ddots & \lambda & \vdots \\ 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^{n-1}a_2\begin{vmatrix} -1 & \ddots & 0 \\ \ddots & \ddots & \lambda \\ \ldots & 0 & -1 \end{vmatrix}\right )+a_1\lambda +a_0\\ & =\lambda^2 \left (\lambda \begin{vmatrix} \lambda & 0 & a_3 \\ \ddots & \lambda & \vdots \\ 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^{n-1}a_2(-1)^{n-3}\right )+a_1\lambda +a_0 \\ & =\lambda^2 \left (\lambda \begin{vmatrix} \lambda & 0 & a_3 \\ \ddots & \lambda & \vdots \\ 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+(-1)^{2n-4}a_2\right )+a_1\lambda +a_0 \\ & =\lambda^3 \begin{vmatrix} \lambda & 0 & a_3 \\ \ddots & \lambda & \vdots \\ 0 & -1 & \lambda+a_{n-1}\end{vmatrix}+a_2\lambda^2+a_1\lambda +a_0\end{align*}
If we aply the Laplace explansion several times, we see that the formula is:
\begin{equation*}\det (\lambda u_n-m_n) =\lambda^n+\sum_{i=0}^{n-1}a_i \lambda^i\end{equation*}

Now we show that this formula is true using induction. (Is the way I do that correct?)

At the base case we have $n=1$, or not? But how is the matrix for $n=1$ ? Do we have that \begin{equation*}\det (\lambda u_1-m_1)=\begin{vmatrix}\lambda \end{vmatrix}=\lambda\end{equation*} ? But then the formula wouldn't hold, would it?

:unsure:
 
Physics news on Phys.org
  • #2
mathmari said:
At the base case we have $n=1$, or not? But how is the matrix for $n=1$ ? Do we have that \begin{equation*}\det (\lambda u_1-m_1)=\begin{vmatrix}\lambda \end{vmatrix}=\lambda\end{equation*} ? But then the formula wouldn't hold, would it?
The question says "let $1\leq n\in \mathbb{N}$", but the matrix $m_n$ does not appear to be defined when $n=1$. In fact, $a_1$ has only one entry, which has to be equal to both $0$ and $-a_0$. I think that the question should have said "let $2\leq n\in \mathbb{N}$" and that you should take the base case to be $n=2$.
 
  • #3
Opalg said:
The question says "let $1\leq n\in \mathbb{N}$", but the matrix $m_n$ does not appear to be defined when $n=1$. In fact, $a_1$ has only one entry, which has to be equal to both $0$ and $-a_0$. I think that the question should have said "let $2\leq n\in \mathbb{N}$" and that you should take the base case to be $n=2$.

Ahh ok! So we have the following:

Base Case: For $n=2$ we have that \begin{equation*}\det (\lambda u_2-m_2)=\begin{vmatrix}\lambda & a_0\\ -1 & \lambda +a_1 \end{vmatrix}=\lambda(\lambda+a_1)-(-1)a_0=\lambda^2+a_1 \lambda+a_0=\lambda^2+\sum_{i=0}^{1}a_i \lambda^i\end{equation*} and so the formula holds. .

Inductive hypothesis: We assume that the formula holds for $n=k$, i.e. \begin{equation*}\det (\lambda u_k-m_k) =\lambda^k+\sum_{i=0}^{k-1}a_i \lambda^i, \ \ \ \ \ (IH)\end{equation*}

Inductive step: We want to show that the formula hodls also for $n=k+1$, i.e. \begin{equation*}\det (\lambda u_{k+1}-m_{k+1}) =\lambda^{k+1}+\sum_{i=0}^{(k+1)-1}a_i=\lambda^{k+1}+\sum_{i=0}^{k}a_i \lambda^i\end{equation*}
We have that
\begin{equation*}\det (\lambda u_{k+1}-m_{k+1})=\begin{vmatrix}\lambda & 0 & \ldots & 0 & a_0 \\ -1 & \ddots & \ddots & \vdots & \vdots \\ 0 & \ddots & \ddots & 0 & \vdots \\ \vdots & \ddots & \ddots & \lambda & \vdots \\ 0 & \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}\end{equation*}
Do we expand as for the first row? Then we would get the following:
\begin{equation*}\det (\lambda u_{k+1}-m_{k+1})=\begin{vmatrix}\lambda & 0 & \ldots & 0 & a_0 \\ -1 & \ddots & \ddots & \vdots & \vdots \\ 0 & \ddots & \ddots & 0 & \vdots \\ \vdots & \ddots & \ddots & \lambda & \vdots \\ 0 & \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}=\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}+(-1)^{k+2}a_0\begin{vmatrix}-1 & \lambda & \ddots & \vdots \\ 0 & \ddots & \ddots & 0 \\ \vdots & \ddots & \ddots & \lambda \\ 0 & \ldots & 0 & -1 \end{vmatrix}\end{equation*}

Now the matrix $\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}$ is a $k\times k$ matrix, but is it of the form$\lambda u_{k}-m_{k}$. so that we can use $(IH)$ ? I ask because at the first row we have now $a_1$ instead of $a_0$. Or do we have to amend the formula of (IH) accordingly?

:unsure:
 
  • #4
The inductive hypothesis should say that the formula holds for every element $(a_0,\ldots,a_{n-1})\in\Bbb{K}^n$. In the inductive argument you start with a $(k+1)\times(k+1)$ matrix whose last column is $(a_0,\ldots,a_{k})\in\Bbb{K}^{k+1}$, and you end up with a $k\times k$ matrix whose last column is $(a_1,\ldots,a_k)$, which is an element of $\Bbb{K}^k$. That is in accordance with the inductive hypothesis. It doesn't matter how the coordinates of that element are labelled.
 
  • #5
Opalg said:
The inductive hypothesis should say that the formula holds for every element $(a_0,\ldots,a_{n-1})\in\Bbb{K}^n$. In the inductive argument you start with a $(k+1)\times(k+1)$ matrix whose last column is $(a_0,\ldots,a_{k})\in\Bbb{K}^{k+1}$, and you end up with a $k\times k$ matrix whose last column is $(a_1,\ldots,a_k)$, which is an element of $\Bbb{K}^k$. That is in accordance with the inductive hypothesis. It doesn't matter how the coordinates of that element are labelled.

Ah ok! So at the inductive step we have the following:
\begin{equation*}\det (\lambda u_{k+1}-m_{k+1})=\begin{vmatrix}\lambda & 0 & \ldots & 0 & a_0 \\ -1 & \ddots & \ddots & \vdots & \vdots \\ 0 & \ddots & \ddots & 0 & \vdots \\ \vdots & \ddots & \ddots & \lambda & \vdots \\ 0 & \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}\end{equation*}
We expand as for the first row:
\begin{equation*}\det (\lambda u_{k+1}-m_{k+1})=\begin{vmatrix}\lambda & 0 & \ldots & 0 & a_0 \\ -1 & \ddots & \ddots & \vdots & \vdots \\ 0 & \ddots & \ddots & 0 & \vdots \\ \vdots & \ddots & \ddots & \lambda & \vdots \\ 0 & \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}=\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}+(-1)^{k+2}a_0\begin{vmatrix}-1 & \lambda & \ddots & \vdots \\ 0 & \ddots & \ddots & 0 \\ \vdots & \ddots & \ddots & \lambda \\ 0 & \ldots & 0 & -1 \end{vmatrix}\end{equation*}
The matrix $\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}$ is a $k\times k$ matrix of the form $\lambda u_{k}-m_{k}$. From the $(IH)$ we get that determiannt is equal to $\displaystyle{\lambda^k+\sum_{i=0}^{k-1}a_{i+1} \lambda^i}$.

The matrix $\begin{vmatrix}-1 & \lambda & \ddots & \vdots \\ 0 & \ddots & \ddots & 0 \\ \vdots & \ddots & \ddots & \lambda \\ 0 & \ldots & 0 & -1 \end{vmatrix}$ is triangular so the determinant is equal to the product of the diagnal elements, i.e. $(-1)^k$.

So we get:
\begin{align*}\det (\lambda u_{k+1}-m_{k+1})&=\lambda \begin{vmatrix} \lambda & 0 & \vdots & a_1 \\ -1 & \ddots & 0 & \vdots \\ \ddots & \ddots & \lambda & \vdots \\ \ldots & 0 & -1 & \lambda+a_{k}\end{vmatrix}+(-1)^{k+2}a_0\begin{vmatrix}-1 & \lambda & \ddots & \vdots \\ 0 & \ddots & \ddots & 0 \\ \vdots & \ddots & \ddots & \lambda \\ 0 & \ldots & 0 & -1 \end{vmatrix} \\ & =\lambda \left (\lambda^k+\sum_{i=0}^{k-1}a_{i+1} \lambda^i\right )+(-1)^{k+2}a_0(-1)^k=\lambda^{k+1}+\lambda\sum_{i=0}^{k-1}a_{i+1} \lambda^i+(-1)^{2k+2}a_0\\ & =\lambda^{k+1}+\lambda\sum_{i=0}^{k-1}a_{i+1} \lambda^i+a_0=\lambda^{k+1}+\sum_{i=0}^{k-1}a_{i+1} \lambda^{i+1}+a_0=\lambda^{k+1}+\sum_{i=1}^{k}a_{i} \lambda^{i}+a_0 \\ & =\lambda^{k+1}+\sum_{i=0}^{k}a_{i} \lambda^{i} \end{align*} Is everything correct? Could we improve something? :unsure:
 

1. What is the formula for calculating a determinant?

The formula for calculating a determinant of a 2x2 matrix is ad - bc, where a, b, c, and d are the elements of the matrix. For larger matrices, the formula becomes more complex and involves finding the products of different elements and taking their sums or differences.

2. Why is the determinant important in linear algebra?

The determinant is important in linear algebra because it is used to determine if a matrix has an inverse. A matrix with a determinant of zero does not have an inverse, and therefore cannot be solved for in linear equations. Determinants are also used to calculate the volume of a parallelepiped and to find the area of a parallelogram or triangle.

3. How does the formula for a determinant relate to the properties of a matrix?

The formula for a determinant is closely related to the properties of a matrix. For example, the determinant of a matrix is equal to the determinant of its transpose, and the determinant of a matrix multiplied by a scalar is equal to the determinant of the matrix multiplied by that scalar raised to the power of the matrix's dimensions.

4. Can the formula for a determinant be used for non-square matrices?

No, the formula for a determinant only applies to square matrices. Non-square matrices do not have a determinant, but they do have a similar concept called the pseudodeterminant, which is used to determine if the matrix has an inverse.

5. Are there any alternative methods for calculating a determinant?

Yes, there are alternative methods for calculating a determinant, such as using row operations to simplify the matrix and then using the properties of determinants to solve for the determinant. Additionally, there are software programs and calculators that can calculate determinants for larger matrices quickly and accurately.

Similar threads

  • Linear and Abstract Algebra
Replies
12
Views
2K
  • Linear and Abstract Algebra
Replies
15
Views
964
  • Linear and Abstract Algebra
Replies
1
Views
1K
  • Linear and Abstract Algebra
Replies
10
Views
2K
  • Linear and Abstract Algebra
Replies
8
Views
1K
  • Linear and Abstract Algebra
Replies
5
Views
2K
  • Linear and Abstract Algebra
Replies
8
Views
1K
  • Linear and Abstract Algebra
Replies
1
Views
728
  • Linear and Abstract Algebra
2
Replies
52
Views
2K
  • Linear and Abstract Algebra
Replies
2
Views
3K
Back
Top