Derivation of Jacobian Determinant

In summary, the Jacobian determinant is used to describe coordinate transformations by relating the areas defined by two vectors in different coordinate systems. The calculation involves taking the cross product of the two vectors, which results in a magnitude represented by the product of the Jacobian determinant and the magnitudes of the two vectors. The use of perpendicular vectors is assumed in this calculation.
  • #1
alt20
3
0
Hi,

I'm having some problems with the derivation of the Jacobian determinant when used to describe co-ordinate transformations. As I understand it, the Jacobian determinant should relate the areas defined by two vectors in both co-ordinate systems. As the vectors are not necessarily perpendicular, the area is calculated using the cross-product, giving:

| dx x dy | = J dudv

(Examples of the derivation can be found http://books.google.co.uk/books?id=...obian determinant area cross product&f=false".)

My problem is that dudv is not a cross product and so doesn't describe the area of a parallelogram in the u-v co-ordinate system. So, as far as I can see it, one of three things is happening:

1) du and dv are assumed to be perpendicular, and so the area is just the product of the sides of the rectange, dudv.

2) du and dv are assumed to be very small, so that the area approximates a rectangle

3) there's something funny about dudv that I haven't spotted - it *is* the product of two vectors, which doesn't actually mean anything I guess. Someone mentioned something about it being a wedge or exterior product...

So yeah, any ideas? What am I missing?

Thanks

James
 
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  • #2
You have some severe misunderstandings, here!

Let [tex]\vec{i},\vec{j}[/tex] be unit vectors in the x,y directions, and let [itex]\vec{u},\vec{v}[/tex] be unit vectors in u,v-directions.

Thus, we have that:
[tex]d\vec{x}=dx\vec{i}=\frac{\partial{x}}{\partial{u}}du\vec{u}+\frac{\partial{x}}{\partial{v}}dv\vec{v}[/tex]
[tex]d\vec{y}=dy\vec{j}=\frac{\partial{y}}{\partial{u}}du\vec{u}+\frac{\partial{y}}{\partial{v}}dv\vec{v}[/tex]

Compute the length of the vector [tex]d\vec{x}\times{d}\vec{y}[/itex] and see what you get!
 
  • #3
Okey dokey. Adding a third dimension to allow the cross product to be calculated:

[tex]d\vec{x} \times d\vec{y}
= \left[\left(\frac{\partial x}{\partial v}dv\right)(0)-(0)\left(\frac{\partial y}{\partial v}dv\right)\right] \vec{i}
+ \left[(0)\left(\frac{\partial y}{\partial u}du\right)-(0)\left(\frac{\partial x}{\partial u}du\right)\right] \vec{j}
+ \left[\left(\frac{\partial x}{\partial u}du\right)\left(\frac{\partial y}{\partial v}dv\right) - \left(\frac{\partial x}{\partial v}dv\right)\left(\frac{\partial y}{\partial u}du\right)\right] \vec{k} [/tex]

[tex] = \left[\left(\frac{\partial x}{\partial u}du\right)\left(\frac{\partial y}{\partial v}dv\right) - \left(\frac{\partial x}{\partial v}dv\right)\left(\frac{\partial y}{\partial u}du\right)\right] \vec{k} [/tex]

Taking the absolute value of the vector:

[tex] \left(\frac{\partial x}{\partial u}du\right)\left(\frac{\partial y}{\partial v}dv\right) - \left(\frac{\partial x}{\partial v}dv\right)\left(\frac{\partial y}{\partial u}du\right) [/tex]

[tex] = \left[\left(\frac{\partial x}{\partial u}\right)\left(\frac{\partial y}{\partial v}\right) - \left(\frac{\partial x}{\partial v}\right)\left(\frac{\partial y}{\partial u}\right)\right]dudv [/tex]

[tex] = J dudv [/tex]

Ah I see, [tex]du[/tex] and [tex]dv[/tex] aren't vectors, they're just magnitudes, right? Is that what you mean?
 
  • #4
QUITE SO!

The AREA dx*dy equals the AREA J*du*dv.
 
  • #5
Ok, but surely that still assumes that [tex]\vec{u}[/tex] and [tex]\vec{v}[/tex] are perpendicular?
 

1. How is the Jacobian determinant calculated?

The Jacobian determinant is calculated by taking the partial derivatives of a set of functions with respect to a set of variables, and then finding the determinant of the resulting matrix.

2. What is the significance of the Jacobian determinant in mathematics?

The Jacobian determinant is an important mathematical tool in multivariate calculus and differential geometry. It is used to calculate the change in variables of a system and measure the rate of change in a multivariate function.

3. Can the Jacobian determinant be negative?

Yes, the Jacobian determinant can be negative. This occurs when the orientation of the coordinate system changes, resulting in a negative value for the determinant. In some cases, this can indicate a change in the direction of a vector or a reversal of the flow of a system.

4. How is the Jacobian determinant used in physics?

In physics, the Jacobian determinant is used to calculate the transformation of variables in a vector field. It is also used in the study of fluid dynamics, where it helps to determine the change in velocity and direction of a fluid at a given point.

5. What are the practical applications of the Jacobian determinant?

The Jacobian determinant has various practical applications in fields such as physics, engineering, and economics. It is used to solve optimization problems, analyze systems of differential equations, and model complex systems. It is also used in computer graphics and image processing to transform and manipulate images.

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