Is the Matrix Positive Definite?

In summary, the conversation discusses a matrix with certain conditions and attempts to show that it is invertible and positive definite. The matrix is written as the sum of two matrices and the positivity of one of them is shown using a specific formula. The other matrix is shown to be positive definite by constructing a similar matrix that is known to be positive definite. There is also a small linguistic note about the correct term for this type of matrix.
  • #1
evinda
Gold Member
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Hello! (Wave)

We have that $q(x) \geq q_0>0, x \in [0,1], h>0$.

Suppose that we have this $(N+1) \times (N+1) matrix$:

$\begin{bmatrix}
\frac{1}{h^2}+\frac{1}{h}+\frac{q(x_0)}{2} & -\frac{1}{h^2} & 0 & \cdots & 0 \\
-\frac{1}{h^2} & \frac{2}{h^2}+q(x_1) & -\frac{1}{h^2} & \cdots &0 \\
0 & & & & \\
& & & & \\
0 & & 0 & -\frac{1}{h^2} &\frac{2}{h^2}+q(x_N)
\end{bmatrix}$

I want to show that it is invertible.

I thought to write it as $Q+T$, where $Q=diag (\frac{1}{2}q(x_0),q(x_1), \dots, q(x_N))$ and

$$T=\begin{bmatrix}
\frac{1}{h^2}+\frac{1}{h} & -\frac{1}{h^2} & 0 & & 0\\
-\frac{1}{h^2} & \frac{2}{h^2} & -\frac{1}{h^2}& &0 \\
0 & -\frac{1}{h^2} & \frac{2}{h^2} & & \\
& & & & -\frac{1}{h^2}\\
& & & -\frac{1}{h^2} & \frac{2}{h^2}
\end{bmatrix}$$But how can we show that $T$ is positive defined?

I have found that $x^T T x=\frac{x_0^2}{2}+\frac{1}{h^2} \sum_{i=0}^{N-1} (x_i-x_{i+1})^2+ \frac{x_N^2}{h^2}$. Is it right? (Thinking)
 
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  • #2
evinda said:
Hello! (Wave)

We have that $q(x) \geq q_0>0, x \in [0,1], h>0$.

Suppose that we have this $(N+1) \times (N+1)$ matrix:

$\begin{bmatrix}
\frac{1}{h^2}+\frac{1}{h}+\frac{q(x_0)}{2} & -\frac{1}{h^2} & 0 & \cdots & 0 \\
-\frac{1}{h^2} & \frac{2}{h^2}+q(x_1) & -\frac{1}{h^2} & \cdots &0 \\
0 & & & & \\
& & & & \\
0 & & 0 & -\frac{1}{h^2} &\frac{2}{h^2}+q(x_N)
\end{bmatrix}$

I want to show that it is invertible.

I thought to write it as $Q+T$, where $Q=diag (\frac{1}{2}q(x_0),q(x_1), \dots, q(x_N))$ and

$$T=\begin{bmatrix}
\frac{1}{h^2}+\frac{1}{h} & -\frac{1}{h^2} & 0 & & 0\\
-\frac{1}{h^2} & \frac{2}{h^2} & -\frac{1}{h^2}& &0 \\
0 & -\frac{1}{h^2} & \frac{2}{h^2} & & \\
& & & & -\frac{1}{h^2}\\
& & & -\frac{1}{h^2} & \frac{2}{h^2}
\end{bmatrix}$$But how can we show that $T$ is positive defined?

I have found that $x^T T x=\frac{x_0^2}{2}+\frac{1}{h^2} \sum_{i=0}^{N-1} (x_i-x_{i+1})^2+ \frac{x_N^2}{h^2}$. Is it right? (Thinking)
For convenience, I'll write $a = 1/h$. Let $S$ be the $(N+1) \times (N+1)$ matrix with $a$'s all down the main diagonal, $-a$'s all down the first super-diagonal, and zeros everywhere else: $$S = \begin{bmatrix}
a & -a & 0 & & 0\\ 0 & a & -a & &0 \\ 0 & 0 & a & & \\ & & & \ddots & -a\\ & & & 0 & a \end{bmatrix}.$$ You can check that $$S^{\textsf{T}}S = \begin{bmatrix}a^2 & -a^2 & 0 & & & 0\\ -a^2 & 2a^2 & -a^2 & & &0 \\ 0 & -a^2 & 2a^2 & & & \\ &&& \ddots && \\ & & & & 2a^2& -a^2\\ & & & & -a^2 & 2a^2 \end{bmatrix}.$$ That is a positive definite matrix. It is almost the same as your matrix $T$, which you can obtain by adding $a$ to the element in the top left corner of $S^{\textsf{T}}S$. That will preserve the positive-definiteness (alternatively you could add $a$ to the first element of the diagonal matrix $Q$). This shows that $T$ is positive definite.
 
  • #3
Is the way I did it wrong? (Thinking)
 
  • #4
evinda said:
Is the way I did it wrong? (Thinking)
Your method is fine. I had not noticed that you already found a solution.
 
  • #5
Opalg said:
Your method is fine. I had not noticed that you already found a solution.

Great! And $Q$ is positive defined since $x^T Q x=\frac{q(x_0)}{2} x_0^2+q(x_1) x_1^2+ \dots+ q(x_N) x_N^2>0$ for $x \neq \overline{0}$ where $x \in R^{N+1}$, right? (Thinking)
 
  • #6
evinda said:
Great! And $Q$ is positive defined since $x^T Q x=\frac{q(x_0)}{2} x_0^2+q(x_1) x_1^2+ \dots+ q(x_N) x_N^2>0$ for $x \neq \overline{0}$ where $x \in R^{N+1}$, right? (Thinking)
Yes! (Star)

Linguistic note: the name for such a matrix is "positive definite", not "positive defined".
 
  • #7
Opalg said:
Yes! (Star)

Great! Thank you! (Smirk)
Opalg said:
Linguistic note: the name for such a matrix is "positive definite", not "positive defined".

A ok... (Nod)
 

FAQ: Is the Matrix Positive Definite?

What does it mean for a matrix to be positive definite?

A matrix is positive definite if all of its eigenvalues are positive. In other words, for any non-zero vector x, the quadratic form xTAx is always positive. This means that the matrix has no negative eigenvalues and all of its pivots are positive.

How can I determine if a matrix is positive definite?

There are several ways to determine if a matrix is positive definite. One method is to check if all of its eigenvalues are positive. Another method is to use the Cholesky decomposition, which involves factoring the matrix into a lower triangular matrix and its transpose. If the matrix can be factored in this way, then it is positive definite.

What are the properties of positive definite matrices?

Positive definite matrices have several important properties. They are always symmetric, meaning that AT = A. They are also invertible, meaning that they have a well-defined inverse. Additionally, positive definite matrices have positive diagonal elements and are always diagonally dominant.

What is the significance of positive definite matrices?

Positive definite matrices have many applications in mathematics and science. They are commonly used in optimization problems, as they guarantee that a local minimum is also a global minimum. They also play a key role in statistics and probability, where they are used to define multivariate Gaussian distributions.

Can a matrix be both positive definite and positive semidefinite?

No, a matrix cannot be both positive definite and positive semidefinite. A matrix is positive semidefinite if all of its eigenvalues are non-negative. This means that it can have zero eigenvalues, while a positive definite matrix cannot have any zero eigenvalues. Essentially, a positive definite matrix is a stricter condition than positive semidefinite.

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