Question on Jacobian determinant

In summary, linear transformations have constant Jacobian determinant. However, the converse is not true as there is a class of transformations called canonical transformations or symplectic transformations that preserve volume but are not necessarily linear. An example of such a transformation is u=ln(x) and v=xy, where x and y are both greater than 0. The Jacobian determinant in this case is constant but the transformation is not linear. This shows that there are infinitely many non-linear transformations with constant Jacobian determinant.
  • #1
mnb96
715
5
Hello,

it is true that linear transformations have constant Jacobian determinant.
Is the converse true? That is, if a transformation has constant Jacobian determinant, then is it necessarily linear?
 
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  • #2
Hello,

Yes, linear transformations have constant Jacobian determinant. You can check this by manual calculation.

The converse is not true. In fact, there is an important class of transformations in physics called canonical transformations (or symplectic transformations) which preserve volume, but which are not, in general, linear.

I wish I had a nice simple example at hand, but perhaps someone else will come along with a good one.
 
  • #3
The total derivative of a linear map is the linear map itself, and in particular, it's constant. The total derivative of a map is just a linearized version of the map at each point. If it's already linear, nothing happens to it when you take its derivative at a point.

Just so we don't get confused, the baby case is 5x, whose derivative is 5. The latter 5 can be interpreted as the linear map that multiplies stuff by 5, so as a linear transformation, it's the same as the first map. For a linear map from ℝ^2 to ℝ^2, the total derivative is a constant linear map, which is represented by a 2 by 2 matrix. The determinant of that matrix is the Jacobian.
 
  • #4
Vargo said:
Hello,

Yes, linear transformations have constant Jacobian determinant. You can check this by manual calculation.

The converse is not true. In fact, there is an important class of transformations in physics called canonical transformations (or symplectic transformations) which preserve volume, but which are not, in general, linear.

I wish I had a nice simple example at hand, but perhaps someone else will come along with a good one.
Don't know much about symplectic transformations, but what about the following one:

##u=\ln x##, ##v=xy##, for ##x>0##, ##y>0##.

This is certainly not linear but

##\partial u/\partial x = 1/x##, ##\partial u/\partial y=0##, ##\partial v/\partial x=y##, ##\partial v/\partial y= x##.

The Jacobian determinant is then ##1/x * x -0*y=1## for all ##x,\,y>0##.

So the Jacobian determinant is constant but the transformation is not linear.
 
  • #5
Hi!
thank you all for the explanations.
Very interesting replies actually!
 
  • #6
nice example erland, and it shows how to construct infinitely more.
 

1. What is the Jacobian determinant?

The Jacobian determinant is a mathematical concept used in multivariable calculus and linear algebra. It is a function that describes the change in variables when transforming from one coordinate system to another.

2. Why is the Jacobian determinant important?

The Jacobian determinant plays a critical role in determining the volume element of a multivariable function, and is used extensively in applications such as optimization, differential equations, and physics.

3. How is the Jacobian determinant calculated?

The Jacobian determinant is calculated by taking the partial derivatives of the variables in the transformation and arranging them in a square matrix. The determinant of this matrix is the Jacobian determinant.

4. What does a negative Jacobian determinant indicate?

A negative Jacobian determinant indicates that the transformation results in a reversal of orientation or direction. This can have implications in certain applications and should be taken into consideration when using the Jacobian determinant.

5. Can the Jacobian determinant be zero?

Yes, the Jacobian determinant can be zero, which indicates that the transformation results in a degenerate or singular point. This means that the transformation is not well-defined at this point and can have implications in certain applications.

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