Jacobian when there's a multivariate function inside it

In summary, the Jacobian of the function F(x,y) = f( g(x)k(y) ; g(x)+h(y) ) will have two columns and two rows due to the variables x and y, and the standard rules for partial differentiation must be augmented with the chain rule to differentiate the multivariate function f inside the Jacobian.
  • #1
gummz
32
2

Homework Statement



differentiate the function F(x,y) = f( g(x)k(y) ; g(x)+h(y) )

Homework Equations



Standard rules for partial differentiation

The Attempt at a Solution



The Jacobian will have two columns because of the variables x and y. But what then? f is a multivariate function inside the Jacobian!
 
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  • #2
So on top of the standard rules you get the chain rule.
Show some attempt at solution and help is on the way.

To demo my ignorance: Differentiating gives two columns, but one row only, right ?
Is there a significance in the ";" ? You write F ( x , y ) -- a notation which I am also familiar with -- , but then you write f ( u ; v )
 
  • #3
gummz said:

Homework Statement



differentiate the function F(x,y) = f( g(x)k(y) ; g(x)+h(y) )

Homework Equations



Standard rules for partial differentiation

The Attempt at a Solution



The Jacobian will have two columns because of the variables x and y. But what then? f is a multivariate function inside the Jacobian!

Do you mean ##F(x,y) = f(u,v)##, where ##u = g(x) k(y)## and ##v = g(x) + h(y)##? If so, just apply the chain rule for derivatives. You need to express the answers in terms of the functions ##f_1, f_2##, where ##f_1(u,v) \equiv \partial f(u,v)/\partial u## and ##f_2(u,v) \equiv \partial f(u,v) / \partial v##.
 
  • #4
Consider the partial derivatives that make up the derivative matrix. It should be a 2x2, you have two functions, and take the derivative of both functions wrt x or wrt y.
 

Related to Jacobian when there's a multivariate function inside it

What is a Jacobian?

A Jacobian is a mathematical concept used in multivariate calculus. It represents the rate of change of a set of variables with respect to another set of variables.

Why is the Jacobian important?

The Jacobian is important because it allows us to calculate the rate of change of a multivariate function, which is essential in many fields of science, such as physics, engineering, and economics.

How is the Jacobian calculated?

The Jacobian is calculated by taking the partial derivatives of a set of variables with respect to another set of variables and arranging them in a matrix. This matrix is then used to determine the rate of change of the function.

What is the relationship between the Jacobian and multivariate functions?

The Jacobian is used to represent the rate of change of a multivariate function. It is often used in conjunction with partial derivatives to analyze the behavior of multivariate functions.

What are some applications of the Jacobian?

The Jacobian has many applications in various fields of science, including optimization, differential equations, and transformations in geometry. It is also used in computer graphics and machine learning algorithms.

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