Understanding Matrix Calculus: Laplacian, Hessian, and Jacobian Explained

In summary, while studying matrix calculus, Jhenrique learned about the definitions of the Jacobian, Hessian, and Laplacian. The Hessian is a 2x2 matrix, the Laplacian is a 1x1 matrix, and the Laplacian is the trace of the Hessian. Jhenrique wondered about a potential mistake in the definitions, as the Laplacian seems to conflict with the definition of the Hessian.
  • #1
Jhenrique
685
4
Hellow!

I was studying matrix calculus and learned new things as:
[tex]\frac{d\vec{y}}{d\vec{x}}=\begin{bmatrix} \frac{dy_1}{dx_1} & \frac{dy_1}{dx_2} \\ \frac{dy_2}{dx_1} & \frac{dy_2}{dx_2} \\ \end{bmatrix}[/tex]
[tex]\frac{d}{d\vec{r}}\frac{d}{d\vec{r}} = \frac{d^2}{d\vec{r}^2} = \begin{bmatrix} \frac{d^2}{dxdx} & \frac{d^2}{dydx}\\ \frac{d^2}{dxdy} & \frac{d^2}{dydy}\\ \end{bmatrix}[/tex]
Those are the real definition for Jacobian and Hessian. However, the definition for Laplacian is ##\triangledown \cdot \triangledown = \triangledown^2##, that corresponds to ##\frac{d}{d\vec{r}} \cdot \frac{d}{d\vec{r}} = \frac{d^2}{d\vec{r}^2}##, but this definition conflicts with the definition for Hessian that is ##\frac{d^2}{d\vec{r}^2}## too. So, where is the mistake with respect to these definitions? I learned something wrong?
 
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  • #2
Hello Jhenrique! :smile:

The Hessian is a 2x2 matrix, (column-vector)(row-vector).

The Laplacian is a 1x1 matrix, (row-vector)(column-vector). :wink:
 
  • #3
The laplacian is the trace of the hessian.
 

Related to Understanding Matrix Calculus: Laplacian, Hessian, and Jacobian Explained

1. What is matrix calculus?

Matrix calculus is a branch of mathematics that deals with the differentiation and integration of matrices and vectors. It is commonly used in statistics, physics, engineering, and other fields to solve problems involving multivariable functions.

2. What is the Laplacian in matrix calculus?

The Laplacian in matrix calculus is a second-order derivative operator that measures the curvature of a function at a particular point. It is represented by the symbol ∇² and is commonly used to find critical points and determine the nature of extrema in multivariable functions.

3. What is the Hessian in matrix calculus?

The Hessian in matrix calculus is a matrix of second-order partial derivatives that measures the curvature of a function in all directions at a particular point. It is represented by the symbol H and is commonly used to determine the nature of critical points in multivariable functions.

4. What is the Jacobian in matrix calculus?

The Jacobian in matrix calculus is a matrix of first-order partial derivatives that represents the linear transformation between two vector spaces. It is commonly used to calculate the rate of change of a multivariable function with respect to its inputs.

5. How is matrix calculus used in real-world applications?

Matrix calculus has a wide range of applications in fields such as machine learning, computer graphics, economics, and physics. It is used to optimize functions in data analysis, solve differential equations in physics, and perform transformations in computer graphics, among many other uses.

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