Jacobian of the linear transform Y = AX

Click For Summary
SUMMARY

The Jacobian of the linear transformation Y = AX, where A is a constant nxn matrix, is definitively the determinant of A. The transformation can be expressed as Y = g(X) = (g1(X), g2(X), ..., gn(X)), where each gi(X) represents a linear combination of the entries in the ith row of A. The discussion confirms that the Jacobian matrix for this transformation is equivalent to the determinant of A, reinforcing the relationship between linear transformations and their Jacobians in multivariable calculus.

PREREQUISITES
  • Understanding of linear algebra concepts, specifically matrix operations.
  • Familiarity with Jacobian matrices and their applications in multivariable calculus.
  • Knowledge of vector-valued functions and their derivatives.
  • Basic proficiency in determinants and their properties.
NEXT STEPS
  • Study the properties of Jacobians in multivariable calculus.
  • Learn about the applications of determinants in linear transformations.
  • Explore vector-valued functions and their derivatives in depth.
  • Investigate the relationship between linear combinations and matrix representations.
USEFUL FOR

Students and professionals in mathematics, particularly those studying calculus and linear algebra, as well as anyone involved in fields requiring the application of Jacobians in transformations.

Legendre
Messages
59
Reaction score
0

Homework Statement



Y = AX = g(X)

Where X,Y are elements of R^n and A is a nxn matrix.

What is the Jacobian of this transformation, Jg(x)?


Homework Equations



N.A.

The Attempt at a Solution



Well, I know what to do in the non-matrix case. For example...

U = g(x,y)
V = h(x,y)

The transformation can be seen as a vector valued function f(x,y) = (g(x,y),h(x,y)). So the jacobian of this transform, Jf(x,y) = the determinant of a matrix with row 1 = [dg/dx , dh/dx] and row 2 = [dg/dy, dh/dy].

So Jf(x,y) = (dg/dx)(dh/dy) - (dg/dy)(dh/dx).

But what do I do in the matrix case? I know g(X) can be seen as a vector with functions as entries but does this help?

Y = AX = g(X) = (g1(X),g2(X),...,gn(X))

Thanks!
 
Physics news on Phys.org
If you mean that A is a constant matrix, then the Jacobian is just the determinant 0f A.
 
I agree with HallsofIvy:

It don't think it matters to have a matrix, I do consider it as a vector of R^n as you do Legendre. Then I write the matrix of Jacobi of this function and find A; so it's jacobian is the determinant of A.
 
Thanks guys. I wrote Ax, for a constant martix A, as a linear combination of its columns, then deduce that each of the gi(X) is a linear combination of the entries in the ith row of A. Then the jacobian is the determinant of A transposed, which is equal to the determinant of A!
 

Similar threads

Replies
2
Views
2K
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 8 ·
Replies
8
Views
6K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K